Top 8 Kubernetes Best Practices to Get the Most out of It

With the growth of cloud technology, several enterprises are now aware of the benefits of adopting hybrid and multi-cloud models. However, when shifted between different cloud environments, they face a set of challenges to ensure the applications' reliable performance. Thus, the introduction of the concept of containers in cloud computing comes into action. Containerization is simply the clustering of an application and all its components into a single, portable suite. With containerization rapidly gaining popularity in cloud computing, leading providers, including Amazon Web Services (AWS), Azure, and Google, offer container services and orchestration tools to accomplish container creation and deployment. Based on Forrester's 2020 Container Adoption Survey, about 65% of entrepreneurs are already using or are planning to implement container orchestration platforms as part of their IT transformation approach. Kubernetes is one of the most known and future-ready, portable container orchestration platforms developed by Google. It is a scalable, reliable, robust, and secured platform, which can manage and accommodate high traffic for cloud applications and microservices. For optimal performance, implementing Kubernetes best practices and following a tailored configuration model is significant to ensure the optimal platform efficiency your enterprise requires.

This article will highlight the top eight best practices of Kubernetes that will help you orchestrate, scale, control, and automate your enterprise applications. But before we start, let us know the basic concept of Kubernetes. 

What is Kubernetes?

Kubernetes (a.k.a. k8s or "Kube") is Google's open-source container management platform spanning public, private, and hybrid clouds that automates numerous manual processes involved in scaling, deploying, and managing the containerized applications. Kubernetes is an ideal platform for hosting cloud-native applications that require quick scaling, like real-time data streaming through Apache Kafka. In simple words, you can cluster together groups of hosts running Linux containers, and Kubernetes supports you in managing those clusters quickly and efficiently. Gartner forecasts that worldwide container management revenue will grow sturdily from a small base of $465.8 million in 2020 to register $944 million by 2024. It seems that the popularity of Kubernetes across the enterprises will make the forecast achievable.

Using Kubernetes, outsourcing the data centers to public cloud service providers, or providing web hosting to optimize software development processes can become manageable. Moreover, website and mobile applications with intricate custom codes can deploy Kubernetes on their product hardware for a cost-effective solution. Moreover, it helps you completely implement and trust a container-based infrastructure in production environments, where you need to manage the containers that run the applications and ensure zero downtime. For example, if a container goes down and another container needs to start, Kubernetes handles the situation with its distributed system framework efficiently. 

Reasons Behind the Popularity of Kubernetes Strategy

Kubernetes is in the headlines, and we hear about it on social media or at user groups and conferences. So, what is the reason behind its popularity? According to the Kubernetes service providers, it has become the standard for container management platform as it offers several advantages:
  • Scalability: It offers easy scalability of the containers across many servers in a cluster through the auto-scaler service, thereby maximizing resource utilization with a simple command, with a UI, or automatically based on CPU utilization.
  • Flexibility: The flexibility of Kubernetes expands for applications to operate consistently and efficiently irrespective of the complexity of the requirement.
  • Storage Orchestration: The open-source attribute of Kubernetes gives you the liberty to take advantage of storage orchestration from different cloud environments and shift the workloads effortlessly to their destinations.
  • Automation: Using Kubernetes, you can automatically place containers as their resource requirements without any availability concerns. It helps to combine critical and best-effort workloads, to drive the utilization and save resources.
  • Health-Check and Self Heal: Kubernetes allows you to perform the health-check and self-heal your containers with auto-replacement, auto-restart, auto-replication, and auto-scaling properties. 
  • Reliability and Security: Kubernetes offers tolerance and clustering of significant errors, bringing stability and reliability to the project. Built-in data encryption, vulnerability scanning, etc., are some of the services of Kubernetes that enhance its security aspect.
  • Self-discovery: Kubernetes allows self-discovery by providing their IP address to the containers and providing a single DNS name to a group of containers.
  • Roll Out and Roll Back Automation: Kubernetes gradually rolls out changes to your application or its configuration while monitoring the application's health to ensure it does not kill all your instances at the same time. Kubernetes rolls back the changes in case of any discrepancy.

8 Kubernetes Best Practices for Efficient Deployment

According to Red Hat's "The State of Enterprise Open-Source Report," 85% of the interviewees agree that Kubernetes is the key to cloud-native application strategies. Kubernetes has evolved from the code that Google used to manage its data centers at scale. Nowadays, organizations use Kubernetes for complete data center outsourcing, web/mobile applications, SaaS support, cloud web hosting, or high-performance computing. For any platform to operate and perform at its optimum capacity, there are certain best practices that you should consider. In this article, we will discuss a few of the best practices of Kubernetes that can improve the efficiency of your production environment.

Use The Latest Version and Enable RBAC

Kubernetes releases new features, bug fixes, and platform upgrades with its consistent version update. As a rule, you must always use the latest version to make sure that you have optimized your Kubernetes. By upgrading to the newest release, you will get technical support and a host of advanced security features to control the potential threats while fixing reported vulnerabilities.

Enabling RBAC (Role-Based Access Control) will help you control access and admittance to users and applications on the system or network. The introduction of RBAC in the Kubernetes 1.8 version helped to create authorization policies using rbac.authorization.k8s.io API group. It allows Kubernetes to permit access to the user, add/remove approvals, set up regulations, etc.

Organize With Kubernetes Namespaces

A namespace is a kind of virtual cluster that helps your Kubernetes environment organize, secure, and perform. Thus, it can be considered one of the Kubernetes best practices that enables you to create logical partitions and apply separation of your resources and restrict the scope of user permissions. Thus, you can use it in a multi-user environment spanning multiple teams or projects.

Namespaces cannot be nested inside one another, and each Kubernetes resource must be in its own unique namespace. However, it is not essential to use multiple namespaces to distinguish slightly unlike resources, such as different releases of the same software: use labels to separate resources within the identical namespace.

Consider Small Container Images

Using base images may include the unnecessary inclusion of additional packages and libraries. Hence it is significant to use smaller container images as it helps you to create a high-performing platform quickly. As one of the Kubernetes best practices, you can consider Alpine Linux Images, which are much smaller than the base images. Alpine Images have access to a package repository that has necessary add-ons. You can add essential packages and libraries for your application as required. Smaller container images are also less vulnerable to security threats as they have lesser attack surfaces.

Setting Up Health Checks

Managing extensive distributed systems can be complex, especially when things are not running perfectly. The primary reason for the complication in the distributed system is that multiple operations work together for the system to function. So, in case of any discrepancy, the system has to identify and fix it automatically. Kubernetes health checks are simple ways to ensure that application instances are working.

Health checks are the effective Kubernetes best practices to analyze whether your system is operational or not. If an instance is non-operational or failed, then other services should not access or communicate with it. As an alternative, the system can divert the requests to some other ready and operational instances. Moreover, the system should bring your app back to a healthy state. Kubernetes provides you two types of health checks, and it is significant to recognize their differences and utilities.

Readiness probes allow Kubernetes to identify whether the application is ready to serve the traffic before permitting the traffic to a pod (most miniature Kubernetes objects). It fundamentally shows the availability of the pod to accept the workload traffic and respond to requests. In case the readiness probe fails, Kubernetes halts the traffic towards the pod until it is successful. 

The liveliness probe allows Kubernetes to perform a health check to verify whether the application operates as desired. In case it fails, Kubernetes removes the pod and initiates its replacement.

Setting Kubernetes Resource Usage (Requests and Limits)

Kubernetes uses the process requests and limits to control resource usages such as CPU and memory. If a container requests a resource, Kubernetes will only map the schedule on a node to provide the requested resource. Whereas limits help to make sure a container never goes beyond a specific request value. The container will be automatically restricted if it goes beyond the limit. 

To get a total resource value of Kubernetes pods (usually available in a group) comprising one or multiple containers, you need to add the limits and requests for each container. While your Kubernetes cluster might be operational without setting the resource 'requests and limits', you will start getting stability issues as the workloads start scaling. Adding 'requests and limits' will help you to get the optimal benefit of Kubernetes.

Discovering External Services on Kubernetes

If you want to discover and access the services living outside your Kubernetes cluster, you can do it by using the external service endpoint or Config Maps directly in your code. Even if you are unwilling to identify those today, there can be a compulsion to do so tomorrow. Mapping your external services to the internal ones will enhance the flexibility to transmit these services into the cluster in the future while reducing recoding efforts. Additionally, it will help you to easily manage and understand the external services your organization is using.

Database Running- Whether to consider or not?

Running a database on Kubernetes can get you some benefits regarding the automation Kubernetes provides to keep the database application active. However, it would help if you analyze them before you start. There can be failure incidents because the pods (database app containers) are susceptible to letdowns compared to a traditionally hosted or fully managed database. Databases with concepts like sharing, failover elections, and replication built into its DNA will be easier to run on Kubernetes. 

Thus, simple questions like the following will help to draw a Kubernetes strategy to consider whether to run a database or not.
  • Are the features of the database Kubernetes-friendly?
  • Are the workloads of the database compatible with the Kubernetes environment?
  • What is the limit of the Ops workload acceptable in the Kubernetes environment?
If the answers to all the questions are affirmative, your external database is ready to run on the Kubernetes environment. Otherwise, you should consider other platforms such as managed DB or VM. 

Termination Practices

Addressing failures is inevitable in distributed systems. Kubernetes helps in handling failures by using controllers that can keep an eye on the state of your system and restart the halted services. However, Kubernetes can also often compulsorily terminate your application as part of the regular operation of the system. It can terminate Kubernetes objects for various reasons because enabling your application to handle these terminations efficiently is essential to create a steady plan and provide a great user experience.

Winding Up

The CNCF survey report 2020 highlights the progressive inclination towards adapting the Kubernetes platform. The survey received 1324 responses inferred in 2020, where 91% of respondents report using Kubernetes, 83% of them are in production, showing a steady upsurge of 78% from last year and 58% in 2018. Adhering to the Kubernetes best practices will provide you an opportunity to take your production environment to the next level and meet the business requirements. In addition, it will have a positive impact on the Kubernetes market size.

Several top marketers and service providers are doing their best to ensure their customers get the desired benefits for Kubernetes deployment in production. Moreover, they also pitch for services on Kubernetes and allow businesses to gain the most out of it. In the latest interview with Media 7, Red Hat's Director of Product Marketing, Irshaad Raihan says, "We look to inspire great ideas and help our customers reach for the impossible. Once we have buy-in into the "why," we arm customers with the most relevant data points to help them make a purchase decision around product and vendor."

FAQ’s

What exactly is Kubernetes?

Kubernetes is an open-source, portable, and scalable platform for container orchestration, automating several manual tasks for managing the containerized workloads. Kubernetes allows clustering running Linux containers and supports managing those clusters quickly and efficiently.

Why is Kubernetes so popular?

Kubernetes has become one of the efficient container management systems as it offers several advantages, such as easy scaling of the containers across many servers in a cluster. It helps in the easy movement of workloads between different types of environments. It also offers high error tolerance, which contributes to the stability and reliability of the workload and has built-in security tools that provide enhanced safety to the platform.

What is an example of Kubernetes?

One of the most popular Kubernetes use cases is the popular game Pokemon Go. Niantic Inc. was the developer and witnessed more than 500 million downloads with 20 million active users every day. Pokemon Go's parent company was not expecting this kind of traffic. As an advanced solution, they opted for Google Container Engine powered by Kubernetes.

Where is Kubernetes used?

You can use Kubernetes to manage microserver architecture. Kubernetes simplifies various facets of running a service-oriented application infrastructure. For instance, it can control the allocation of resources and drive traffic for cloud applications and microservices.

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Cloud Storage

10 Data Warehouse Best Practices to Save Colossal Extra Costs

Article | February 20, 2024

Storing large data sets in a data warehouse can become expensive over a period of time. However, data warehouse best practices save organizations colossal cloud storage costs and optimize them. Contents 1. The High Cost of Low-efficiency Data Warehousing 2. Data Warehouse Best Practices: A Blueprint to Savings 2.1 Effective Data Organization 2.2 Automation 2.3 Storage Optimization 2.4 Data Quality Assurance 2.5 Security Measures 2.6 Metadata Management 2.7 Logging 2.8 Data Flow Diagram 2.9 Change Data Capture (CDC) Policy 2.10 Agile Data Warehouse Methodology 3. The Future is Frugal: Tapping Cost-effective Data Warehousing Inefficient data warehousing can be a silent drain on an organization's resources, necessitating the implementation of stringent data warehousing best practices. It's like a leaky faucet, slowly siphoning off valuable time and money, often going unnoticed until the damage is done. The financial implications are far-reaching, from increased storage costs to wasted resources and even the potential for costly errors. 1. The High Cost of Low-efficiency Data Warehousing Increased Storage Costs: Inefficient data warehousing can lead to unnecessary data duplication and overlap, resulting in high storage costs. Wasted Resources: Poorly managed data warehouses often consume up to 90% of the available compute capacity and 70% of the required storage space. Potential for Costly Errors: Manual errors and missed updates can lead to corrupt or obsolete data, affecting data-driven decision-making and causing inaccurate data analysis. Efficiency in data management is not just about cutting costs; it's about unlocking the full potential of the existing data. It is crucial to understand the best practices for data warehousing to save costs and aim to turn data warehouses from a cost center into a value generator. 2. Data Warehouse Best Practices: A Blueprint to Savings Data warehousing is an essential aspect of business intelligence which often presents operational challenges. The tasks can be daunting, from managing vast amounts of data to ensuring data quality and security. However, by adopting best practices, these challenges can be turned into opportunities for significant cost savings. Data warehouse cost optimization drives the success of a data warehouse, mitigating the challenge of reducing data warehouse costs in the long run. 2.1 Effective Data Organization Structured Data Modeling and Design: A well-thought-out data model organizes data effectively, enabling efficient data retrieval and supporting analytics needs. Metadata Classification: By categorizing data based on metadata, organizations can significantly enhance data retrieval and organization. Data Governance: Implementing a data governance framework helps define the relationships between people, processes, and technologies. Data Warehouse Schema Design: A well-designed schema optimizes data retrieval and analysis and ensures that the data warehouse aligns with the business’s analytical and reporting needs. Data Flow Management: Efficient management of data flow from various sources into the data warehouse is crucial for maintaining data integrity and consistency. Effective data organization involves structuring data in a way that facilitates efficient retrieval and analysis. It requires a well-thought-out data model, effective metadata classification, robust data governance, appropriate schema design, and efficient data flow management. 2.2 Automation ETL Automation: Automating ETL processes decreases the human labor required to build and deploy warehouses. Data Integration Automation: Automating data integration ensures smooth data flow into a warehouse. Data Quality Checks Automation: Implementing automated data quality checks minimizes the risk of erroneous data analysis. Data Warehouse Design Automation: Modern data warehouse design tools can execute within hours, compared to months, at a fraction of the cost of manual programming. Data Management Automation: Automation in data management can drastically reduce manual labor and error rates. Data warehouse automation replaces standard methods for building data warehouses with the right data warehousing software tools. It automates the planning, modeling, and integration steps, keeping pace with an ever-increasing amount of data and sources. A data warehouse software buyer’s guide comes in handy to select the appropriate tool for data center operations. 2.3 Storage Optimization Efficient Data Analysis: Supports complex data queries and analytics, enabling deeper insights and more effective reporting. Scalability and Flexibility: It adapts easily to changing data volumes and evolving business needs. Data Compression: Data compression techniques can be used to reduce the storage space required. Data Partitioning: Data partitioning can improve query performance and the manageability of data. Data Indexing: Proper indexing can significantly speed up data retrieval times. Storage management and optimization in data warehousing involve techniques that improve performance and reduce storage costs. 2.4 Data Quality Assurance Data Cleansing: This involves identifying and fixing errors, duplicates, inconsistencies, and other issues. Data Validation: This ensures the accuracy, consistency, and reliability of the data stored in a warehouse. Data Profiling: It entails understanding the quality of data to uncover any gaps. Data Standardization: The process ensures that the data conforms to common formats and standards. Continuous Monitoring: Regular monitoring of data quality is necessary to maintain high standards. Data quality assurance involves identifying and fixing errors, duplicates, inconsistencies, and other issues. It ensures the accuracy, consistency, and reliability of the data stored in a company’s warehouse. 2.5 Security Measures User Access Controls: This is for ensuring strict user access controls so that employees only have access to the data they need to conduct their tasks. Data Encryption: This is done using highly secure encryption techniques to protect data. Network Security: It takes precautions to safeguard networks where data is stored. Data Migration Security: Moving data with care and consideration for the security implications of any data migration process comes under data migration security. Regular Security Audits: This implies conducting regular security audits to identify potential vulnerabilities. Security measures in data warehousing involve using a multiplicity of methods to protect assets. These include intelligent user access controls, proper categorization of information, highly secure encryption techniques, and ensuring strict access controls. 2.6 Metadata Management Data Cataloging: This is all about maintaining a comprehensive catalog of all data assets to facilitate easy retrieval and usage. Data Lineage: Data lineage allows you to trace the origin and transformation of data over its lifecycle. Data Dictionary: A data dictionary is used to define the meaning, relationships, and business relevance of data elements. Metadata Integration: This is essential for seamless integration of metadata across various platforms and tools. Regular Metadata Updates: Regularly updating metadata is done to reflect changes in data sources and business requirements. Metadata management in data warehousing involves the systematic organization and control of data assets. This includes maintaining a comprehensive data catalog, tracking data lineage, creating a data dictionary, and ensuring seamless metadata integration. 2.7 Logging Activity Tracking: The activity implies monitoring user activities and transactions to maintain a record of data interactions. Error Logging: Capturing and recording errors facilitates troubleshooting and improves system reliability. Audit Trails: Maintaining audit trails ensures accountability and traceability of actions. Log Analysis: Regularly analyzing log data helps in the identification of patterns, anomalies, and potential security threats. Log Retention: Storing logs for a defined period assists in meeting compliance requirements and supports incident investigation. Logging in data warehousing involves keeping a detailed record of activities, errors, and transactions. This includes monitoring user activities, capturing errors, maintaining audit trails, analyzing log data, and storing logs as per compliance requirements. 2.8 Data Flow Diagram Data Sources: Data sources involve identifying and documenting the sources from which data is collected. Data Transformation: The task entails mapping out the processes that modify or transform data as it moves through the system. Data Storage: Data storage involves detailing where data is stored at various stages of the data lifecycle. Data Usage: This illustrates how and where data is used in business processes. Data Archiving: The process shows how data is archived or retired when no longer in active use. A data flow diagram in data warehousing provides a visual representation of how data moves, transforms, and is used within the system. It includes identifying data sources, mapping data transformations, detailing data storage, illustrating data usage, and showing data archiving processes. 2.9 Change Data Capture (CDC) Policy Understanding Data Needs: One begins the incorporation of CDC by understanding the data integration requirements. Choosing the Right CDC Method: One chooses a CDC method that resonates with the requirements and specific use cases. Incorporating Monitoring and Logging Processes: The process involves the implementation of proper recording and monitoring mechanisms to evaluate the quality and efficacy of the CDC tools. Ensuring Real-Time Synchronization: Change data capture helps to synchronize data in a source database with a destination system as soon as a change happens. Choosing the Right CDC Implementation Pattern: Depending on specific needs, one can choose from query-based CDC, trigger-based CDC, or binary log-based CDC. These practices to implement a CDC policy help boost the efficiency of data warehousing operations, leading to significant cost savings. 2.10 Agile Data Warehouse Methodology Model Just-in-Time (JIT): One begins the incorporation of Agile Data Warehouse Methodology by modeling details in a Just-in-Time (JIT) manner. Prove the Architecture Early: The architecture is tested using code early in the process to confirm that it works. Focus on Usage: One prioritizes the needs of the end-users and ensures that the data warehouse or business intelligence solution meets their actual needs. Don’t Get Hung Up on “The One Truth”: One validates and reconciles different versions of the truth within an organization. Organize Work by Requirements: One organizes the development work based on the requirements of the stakeholders. Active Stakeholder Participation: One ensures active participation from all stakeholders. This helps in understanding their needs and expectations better. Strong Collaboration: One reassures that business users and stakeholders work together effectively, as well as that automation, evolutionary modeling, and continuous integration are implemented correctly. Agile data warehousing practices contribute to the efficiency and effectiveness of data warehousing operations, leading to significant cost savings. Each of these best practices contributes to cost savings by reducing data management procedures and increasing overall efficiency. In the next section, learn about cost-effective data warehousing recommendations for the future. Understand how to optimize data warehousing operations further for maximum savings! 3. The Future is Frugal: Tapping Cost-effective Data Warehousing Data warehousing is a crucial component of any data-driven organization. However, the cost of managing and storing vast amounts of data can be a significant pain point. But what if a company could turn this challenge into an opportunity for innovation and sustainability? Frugality, the practice of being economical with resources, is driving significant advancements in data warehousing. Here are some key trends: Cloud Dominance: The shift towards cloud-based data warehousing solutions is accelerating. These platforms offer remarkable scalability, flexibility, and cost-effectiveness. Cost-effective Data Storage: Strategies like data compression, data archival, and resource management are being employed to reduce the overall cost of storing and managing data. Efficient ETL Processes: Optimized ETL processes and seamless data integration ensure smooth data flow into a warehouse, reducing operational costs. Looking ahead, it's clear that frugality will continue to shape the future of data warehousing. So, how can a company tap into these trends for a better future in data warehousing? Firstly, organizations should consider transitioning their data warehouses to the cloud if they haven't already. The cost savings, scalability, and flexibility offered by cloud-based solutions are too significant to ignore. Secondly, they should implement cost-effective data storage strategies such as data compression and archival. Lastly, they should optimize their ETL processes for efficient data integration. By embracing frugality, organizations are not just cutting costs; they are driving innovation and sustainability in their data warehousing operations. The future is indeed frugal!

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Cloud App Development, Cloud Security, Cloud App Management

10 New Innovations in Storage Management for Data Access Control

Article | July 21, 2023

Control data access with novel innovations in cloud data storage management. Discover new ideas like DNA data storage, blockchain data storage, LLMs, and more for data storage management in the cloud. 1. Storage Management: A Puzzle 2. The Innovative Leap in Data Accessibility 2.1 Large Language Models (LLMs) 2.2 DNA Data Storage 2.3 Diamond Data Storage 2.4 Blockchain Data Storage 2.5 Hybrid Cloud Data Storage 2.6 Edge Computing Data Storage 2.7 Zero-trust Data Storage 2.8 Green Data Storage 2.9 Holographic Data Storage 2.10 Federated Data Storage 3. Powerful Data Storage Management in the Cloud 3.1 Backblaze 3.2 BVR Cloud 3.3 DreamHost 3.4 IDriveInc 3.5 Qumulo 3.6 Redstor 3.7 Scaleway 3.8 Unitrends 3.9 Wasabi Technologies 3.10 Zadara 4. Envisioning Cloud Storage Management’s Future The rising cost of cloud storage is a conundrum that businesses grapple with, and this is leaving companies with a dire need for cloud storage management innovations. Google recently announced a significant increase in cloud storage costs, between 25 and 50 percent. This surge, often referred to as ‘cloud-flation,’ has been a catalyst for businesses to seek innovative solutions to optimize their cloud storage space. 1. Storage Management: A Puzzle AI-driven storage solutions are revolutionizing the cloud storage cost conundrum. By analyzing data relevancy, these systems reduce costs and ensure easy accessibility. They also forecast demand, enabling strategic reservations of applications or storage resources, a practice often termed ‘cloud cost optimization.’ This innovation is yielding manifold benefits. Businesses are curtailing expenditure, enhancing resource efficiency, gaining budget control, and improving transparency. With 94% of IT leaders reporting rising cloud storage costs, AI-driven methods are a game-changer, offering a solution to the cloud cost puzzle. This is not just a cost-saving measure but a strategic move towards efficient and effective storage management, adhering to storage management best practices and the latest trends in storage management. It's a testament to the adage, ’Every cloud has a silver lining.’ 2. The Innovative Leap in Data Accessibility Data accessibility is crucial for organizations to utilize data for decision-making and innovation. Current innovations in storage management enable control over data access across platforms, managing who, what, when, where, and how data is accessed. 2.1 Large Language Models (LLMs) LLMs are expected to transform data practices by enabling better capture, classification, and cleaning of data. These help businesses leverage data for various purposes, such as content generation, sentiment analysis, and knowledge extraction. However, LLMs also pose challenges, such as data quality, ethics, and security. Advances in AI ethics and security measures are addressing data quality issues. New techniques for data anonymization and encryption ensure the ethical use of data. 2.2 DNA Data Storage DNA data storage is projected to offer a long-term and high-density solution for data storage. This is because it has the ability to store up to 215 petabytes of data per gram of DNA. It also enables data access control by using molecular cryptography, biometric authentication, and error correction codes. However, DNA data storage also faces hurdles, such as cost, speed, and scalability. Tech advancements in storage reduce the cost of DNA synthesis and sequencing. Parallel processing techniques improve the speed and scalability of DNA data storage. 2.3 Diamond Data Storage Diamond data storage is envisioned to offer a fast, secure, and stable solution for data storage, as it stores data in nanoscale diamonds using laser pulses. It also supports data accessibility by allowing parallel processing and quantum communication. Nonetheless, diamond data storage also requires further research, development, and testing. Ongoing research is optimized for the use of laser pulses for data storage. Quantum communication protocols are enhancing data accessibility in diamond data storage. 2.4 Blockchain Data Storage Blockchain data storage is anticipated to offer a secure, transparent, and immutable solution for data storage. It stores data in a distributed ledger system across multiple nodes. It also facilitates data access control by using smart contracts, encryption, and consensus mechanisms. Yet, blockchain data storage also has limitations such as performance, scalability, and interoperability. Improvements in blockchain technology improve its performance and scalability. Cross-chain communication protocols address the interoperability issues. 2.5 Hybrid Cloud Data Storage Hybrid cloud data storage uses a combination of public and private cloud services to store data to offer a flexible, scalable, and cost-effective solution for data storage. It improves data accessibility by enabling workload portability, unified management, and automation. However, hybrid cloud data storage presents several issues, including complexity, security, and governance. Automation and AI make it easy to manage hybrid cloud environments. Advanced security measures address data security and governance issues. 2.6 Edge Computing Data Storage Edge computing data storage is predicted to offer a low-latency, low-bandwidth, and low-energy solution for data storage. This is owing to the fact that it uses devices at the edge of the network to store and process data. It also enhances data access control by using local encryption, authentication, and caching. However, edge computing data storage confronts challenges such as reliability, compatibility, and maintenance. Edge gadgets are becoming more reliable as technology advances. Compatibility and maintenance issues are being addressed through standardization and remote device management. 2.7 Zero-trust Data Storage Zero-trust data storage is projected to offer a robust, resilient, and reliable solution for data storage, as it employs a security model that assumes no trust between data users and providers. It improves data accessibility by using granular policies, continuous monitoring, and verification. Yet, zero-trust data storage also requires a paradigm shift, a holistic approach, and a cultural change. The adoption of zero-trust principles is becoming more widespread, facilitated by advances in identity and access management technologies. Continuous monitoring and verification techniques are enhancing data security. 2.8 Green Data Storage Green data storage is envisioned to offer an eco-friendly, energy-efficient, and sustainable solution for data storage, as it uses environmentally friendly methods to store data. It promotes data accessibility by using renewable energy sources, energy-efficient devices, and data center optimization. Nonetheless, green data storage demands more awareness, innovation, and investment. Increased awareness of environmental issues drives investment in green data storage. Innovations in energy-efficient storage technologies and renewable energy sources are making data storage more sustainable. 2.9 Holographic Data Storage Owing to its use of laser beams to store data in three dimensions, holographic data storage is anticipated to offer a high-capacity, high-speed, and high-quality solution. It enables data access control by using optical encryption, multiplexing, and hologram authentication. Yet, holographic data storage also faces challenges , which include cost, compatibility, and durability. Technological advancements reduce the cost of holographic data storage. Compatibility issues are being addressed through the development of universal data formats and interfaces. 2.10 Federated Data Storage Federated data storage is expected to offer a privacy-preserving solution. It will also respect sovereignty and improve diversity. This is achieved by storing data across a network of independent data repositories. It also improves data accessibility by using metadata, query processing, and data integration. On the flip side, federated data storage has some drawbacks, such as heterogeneity, latency, and coordination. Advances in privacy-preserving technologies enhance the security of federated data storage. Sovereignty-respecting mechanisms and diversity-enhancing techniques make data storage more inclusive. 3. Powerful Data Storage Management in the Cloud As data volumes explode, businesses grapple with complex access control challenges. This section unveils robust tools that streamline storage management, fortify data access control, and empower decision-makers to navigate the cloud’s vast expanse with confidence. 3.1 Backblaze Backblaze's B2 Cloud Storage is a revolutionary solution that empowers organizations to innovate and elevate their cloud data storage management. It offers infinitely scalable, cost-effective, and S3-compatible storage. This makes it an ideal choice for both personal and business use. The service is enterprise-ready, providing secure and compliant storage with predictable pricing, free of hidden fees and deletion penalties. It's readily accessible, ensuring fast data usage with a 99.9% uptime SLA. Backblaze's cloud storage is durable and reliable, optimizing for data mobility, performance, and cost. It supports data retention and deletion policies, HIPAA programs, and SSAE-18/SOC 2 data centers, making it a trusted choice for decision-makers in any organization. 3.2 BVR Cloud BVR Cloud is a dynamic American cloud hosting company that provides a diverse range of cloud products. Its robust offerings, like virtual machines and managed satellites, facilitate seamless cloud protection and storage. BVR Cloud's low-latency network and frequent upgrades from SSD to NVMe across all locations ensure superior performance. It addresses the critical need for data storage, security, and management of large volumes of data in the cloud. With its 24/7 support, BVR Cloud is a strategic choice for companies aiming to innovate and elevate cloud data storage management. 3.3 DreamHost DreamHost is a trailblazer in the cloud storage ecosystem, offering DreamObjects, a cost-effective and scalable cloud storage service. It's powered by Ceph, ensuring high fault tolerance by storing data on multiple disks across multiple servers. DreamObjects is S3 compatible, making it ideal for hosting files, storing backups, and developing web apps. It offers flexible and predictable pricing with free API requests, catering to the needs of decision-makers. DreamObjects lets organizations innovate their cloud data storage management and therefore, becomes strategic choice for business growth. 3.4 IDriveInc IDriveInc is a pioneering company specializing in cloud storage. It also offers various services, including online backup, file sharing, remote access, compliance, and related technologies. Its product, IDrive, offers comprehensive cloud backup and storage solutions. IDrive comes with several features, such as 256-bit AES encryption, incremental and compressed transfers, and offline file access. IDrive's user-friendly interface is compatible across many operating systems and devices, making it a strategic choice for decision-makers. With IDrive, organizations transcend their cloud data storage management, ensuring secure and efficient handling of large volumes of data. 3.5 Qumulo Qumulo is a leading provider of cloud data storage solutions that offers exabyte-scale file storage in the cloud. Its product, Qumulo's Scale Anywhere platform, is a unified, unstructured data platform that can run and scale everywhere data is created, stored, and accessed. It offers real-time data visibility, AI/ML-powered data prefetch, and continuous data protection. Qumulo's powerful solution empowers organizations to transform their cloud data storage management, guaranteeing safe and efficient handling of extensive data volumes. 3.6 Redstor Redstor is a leader in data protection. It offers a cloud-first backup solution that streamlines data storage management. Its automated and scalable cloud storage ensures secure data recoveries, bolstering organizational resilience. The InstantData technology enables rapid system recovery that minimizes downtime. With AI-powered malware detection and data insights, Redstor empowers organizations to safeguard their data. This makes it an invaluable asset for the IT departments. 3.7 Scaleway Scaleway, a European cloud provider, offers innovative cloud storage solutions that empower organizations to optimize their data management. Its products, including object storage and block storage, provide robust performance, security, and cost adaptability. By transitioning to Scaleway's storage-as-a-service model, organizations can potentially reduce their storage infrastructure costs by 40%. This shift not only offers financial benefits but also enhances data accessibility, scalability, and resilience. From startups to large enterprises, Scaleway's cloud storage solutions are designed to meet diverse needs, driving business growth and continuity. 3.8 Unitrends Unitrends, a trailblazer in cloud data storage management, offers a comprehensive suite of solutions that empower organizations to innovate and elevate their data management strategies. Its flagship product, Unitrends Unified Backup, provides robust data protection, proactive ransomware detection, and seamless integration with various hypervisors. The product's role-based access control model allows granular management of data. This ensures a secure and efficient data handling. With its focus on business continuity and disaster recovery, Unitrends caters to diverse organizational functions, enhancing resilience and reducing downtime. 3.9 Wasabi Technologies Wasabi Technologies, an early innovator in cloud storage, offers a unique solution to enable organizations to manage their data efficiently. Its product, Wasabi Hot Cloud Storage, provides affordable and instant access to data, eliminating complex tiers and unpredictable fees. The product's robust access control mechanisms, such as bucket policies and Access Control Lists (ACLs), ensure secure data management. It also offers multi-user authentication, adding an extra layer of security. Wasabi's solution is beneficial across various functions of an organization. It aids in data backup and recovery, active archiving, surveillance storage, and data lakes. This makes it a vital tool for IT leaders, allowing them to innovate and manage cloud data storage. 3.10 Zadara Zadara is an expert in enterprise storage solutions. It enables businesses to elevate their cloud data storage management with a secure-by-design infrastructure, ensuring stringent data access control. Zadara's platform supports any data type and protocol and can be deployed anywhere, providing unparalleled flexibility. It is an attractive choice for decision-makers owing to its pay-as-you-go model, which optimizes costs. From IT to finance, various functions within an organization can leverage Zadara's solutions for efficient data management. 4. Envisioning Cloud Storage Management’s Future Due to the growth of digital data and the adoption of cloud computing, data storage technology is dynamically evolving. The storage management market, influenced by the increasing use of storage management tools, is set to grow at a CAGR of 11.3%. However, data security and privacy concerns pose challenges. Yet, these hurdles catalyze the development of robust and secure solutions, leading to a demand for a comprehensive storage management software comparison guide. With 56% of respondents using Microsoft Azure, the choice of cloud provider is crucial for performance and cost-efficiency. Summing up, the future of data storage technology is a mosaic of opportunities and challenges, leading to more efficient, secure, and cost-effective solutions. Overcoming them is a journey of optimism and resilience with the help of storage management innovations.

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Cloud Security, Cloud App Management, Cloud Infrastructure Management

15 Fantastic Storage Management Tools for Better Data Analysis

Article | August 1, 2023

Manage vast amounts of data to derive business intelligence with cloud storage management tools and save on rising cloud storage costs. Discover great cloud data management tools for all businesses. Contents 1. Descriptive to Prescriptive Data Analysis in Storage Management 2. High-Performance Storage Management Tools for Data Analysis 3. New Technology Trends Forecast for Storage Management Data is precious for businesses. However, storing and organizing data in the cloud is getting more expensive. So, there’s a growing need for better tools to manage cloud data storage. It’s important to clean and organize data for a comprehensive analysis. Organizations are thinking about moving from descriptive to prescriptive data analysis to speed up decisions based on data. This could significantly change how cloud data is stored and managed. Prescriptive analysis is replacing descriptive analysis, which looks at historical data. This uses insights to suggest actions for the best storage management. This change helps businesses to understand their past and current storage needs. It also guides them in predicting and managing future needs. They do this by using advanced data analysis techniques for smart storage management innovations. Descriptive to Prescriptive Data Analysis in Storage Management Descriptive analysis is a crucial aspect of business intelligence. It uses data collection and mining to organize past data, presenting it in comprehensible visuals. It aims to depict past events, helping decision-making by identifying patterns in past issues. Prescriptive analytics provides forecasts based on past data. It aims to identify the optimal outcome from various options using complex algorithms and raw data analysis. In storage management, addressing sudden data requirements involves more than transitioning from descriptive to prescriptive analysis. Businesses analyze past storage use and employ lateral thinking to uncover unclear patterns or trends. These insights aid in predicting future storage needs and suggesting optimal storage management best practices and strategies. Employing prescriptive analysis in storage management can result in significant cost savings and efficiency enhancements. Lateral thinking helps organizations maximize their storage resources, reduce costs, and improve service delivery and uptime. High-Performance Storage Management Tools for Data Analysis High-performance storage management tools are changing how data is managed in storage systems. They automate tasks such as setup, data placement, and optimization by leveraging AI and machine learning. They unify and manage storage resources across various cloud environments for efficient management. Besides enhancing storage performance, these tools ensure data security and compliance with global storage regulations. Amazon S3 Adapter for SAP CPI Amazon S3 Adapter for SAP CPI offers a range of benefits for organizations managing cloud data storage and analysis: Robust and Scalable: It provides robust and scalable solutions for cloud data storage management. This functionality enables organizations to elastically scale and optimize their storage footprint. Versatile: The adapter supports several protocols, including S3, SQS, SNS, and SWF, enhancing its versatility. Cost-Efficient: By leveraging this adapter, businesses can create a cost-efficient environment. Supports Large Data Infusions: It supports large data infusions, facilitating effective data analysis. User-friendly Web Services Interface: Its simple web services interface lets the developers store and retrieve any amount of data at any time, from anywhere on the web. These features make the Amazon S3 Adapter for SAP CPI an ideal choice for organizations that seek secure, efficient, and scalable cloud data storage solutions. BigMIND BigMIND, a cloud hosting product, offers a range of benefits for organizations managing cloud data storage and analysis: Intelligent Data Management: It leverages AI-driven algorithms to automatically categorize and tag uploaded data, enhancing data retrieval and streamlining data analysis. Advanced Search Capabilities: Its advanced search capabilities empower organizations to optimize decision-making processes. Robust Security Measures: It ensures the safety of stored information with robust security measures, including encryption and data protection. Ease of Use: It boasts an easy-to-use interface and excellent customer support. Novel Features: It has some novel features, including photo facial recognition powered by artificial intelligence and the ability to link services such as Facebook and Google Drive. These features make BigMIND an excellent choice among data management tools in 2024 for decision-makers in the IT and data management sectors of an organization looking for secure, efficient, and scalable insight-driven storage solutions. Cloud Object Storage by Aruba Aruba’s Cloud Object Storage offers a range of benefits for organizations managing cloud data storage and analysis: High Storage Power: Aruba’s Cloud Object Storage offers high storage power, enabling real-time data analytics that accelerate insights and generate business value. Resilient System: Its resilient, self-healing system ensures no downtime during updates, optimizing operational efficiency. Parallel Architecture: The parallel architecture handles large volumes of traffic and requests per second, accelerating data processing. Enhanced Data Security: Its distributed intelligence system eliminates vulnerabilities and improves data security. S3-Compatible API: Lastly, its S3-compatible API adapts to customer needs in real-time, providing a flexible, efficient solution for data management. With these features, Aruba’s Cloud Object Storage emerges as an outstanding option for IT and data management sector executives seeking secure, efficient, and scalable cloud data storage solutions and data storage management tools. Cloudian HyperStore Cloudian HyperStore is an enterprise object storage solution. It offers a range of benefits for organizations managing cloud data storage and analysis: Performance Maximization: It maximizes the performance of AI workloads with an infinitely scalable data lake, enabling real-time data analytics that accelerate insights and generate business value. Robust Data Protection: It ensures robust data protection with military-grade security and data immutability. Simplified Management: It simplifies management and reduces costs through unified file and object consolidation. Geo-Distributed Architecture: Its geo-distributed architecture allows for storage deployment anywhere, optimizing data availability and performance. Complete Data Control: Cloudian offers complete control over data location while providing the scale and simplicity of cloud-native data management. These features make Cloudian HyperStore ideal for organizations looking for secure, efficient, and scalable cloud data storage solutions and a tool for storing and organizing data. DataCore Software-Defined Storage DataCore’s Software-Defined Storage (SDS) offers a range of benefits for organizations managing cloud data storage and analysis: Flexibility: It separates provisioning, data protection, and data placement functions from physical hardware. This feature allows organizations to upgrade, expand, or replace storage hardware without disrupting operational procedures. Cost Optimization: It optimizes IT costs through automation across hybrid storage and offers the freedom to choose any storage vendor, model, or type. Performance Enhancement: It enhances application response speed while lowering hardware spending. Advanced Caching and Parallel I/O: Its advanced caching and patented parallel I/O technology eliminate critical bottlenecks in I/O processing, crucial for faster hosts and flash arrays. Comprehensive Metrics: It provides an impressive array of storage metrics for disks and DataCore servers. These features make DataCore SDS one of the top tools for future data management for secure, efficient, and scalable cloud data storage. DefendX Mobility DefendX Mobility, a solution for cloud data storage management, offers several advantages for organizations: Cost Efficiency: It minimizes file storage costs by redirecting storage growth to less expensive on-premise or cloud-based storage solutions. Enhanced Backup: It enhances backup efficiency through seamless, open, policy-based tiering and archiving. Risk Reduction: It reduces risk and enables disaster tolerance through off-site and cloud-based copies of important data. Vendor Independence: It eliminates vendor lock-in through its standards-based, open software architecture and file migration. Simplified Adoption: It simplifies adoption with a seamless user experience and a phased implementation schedule. These capabilities make DefendX Mobility ideal for decision-makers looking for secure, efficient, and scalable cloud data storage solutions. Fusion Connect: Managed Communications Fusion Connect, a Managed Connectivity Provider (MCP), offers a suite of benefits for organizations managing cloud data storage and analysis: Optimized Connectivity: It maximizes network uptime, ensuring uninterrupted access to cloud-stored data for seamless data analysis. Secure Communications: With comprehensive Unified Communications tools, it facilitates secure virtual meetings, file sharing, and calls from any device. Enhanced Productivity: Streamlining communication across all functions of an organization boosts productivity. Reliable Performance: Delivering the fastest network and wireless speeds enhances the efficiency of data analysis processes. Scalable Solutions: Its services are scalable, catering to the evolving needs of organizations in managing cloud data storage. These features make Fusion Connect ideal for organizations looking for secure, efficient, and scalable cloud data storage solutions. Kdan Cloud Kdan Cloud is a robust solution for cloud data storage management. It offers significant features that enhance an organization’s data analysis capabilities. Streamlined Organization: It allows users to efficiently manage and organize documents, PDF files, animations, videos, and other projects. Enhanced Collaboration: It fosters seamless collaboration among team members with features like link sharing and shared folders. Secure Storage: It ensures the security of user data with TLS/SSL and RSA encryption and offers password protection for shared files. Integrated Functionality: It is fully integrated with other Kdan products, including PDF Reader, Animation Desk, NoteLedge, Markup, and Write-on Video. Accessible Anytime, Anywhere: Access files on Kdan Cloud remotely anytime, facilitating on-the-go data analysis. These functionalities of Kdan Cloud provide data that is secure and organized. Thus, encouraging collaborative work environments. MinIO MinIO is a high-performance, cloud-native object storage system that lets organizations access robust data analysis capabilities: Efficient Data Management: It ensures data integrity and reliability through inbuilt erasure-code and bitrot protection. Scalability: Its multi-tenant scalability makes it ideal for large-scale data storage and analysis. Versatile Integration: It integrates seamlessly with data analytics platforms, providing a high-throughput backend for streaming data analytics. Hardware Agnostic: Its storage hardware-agnostic feature allows easy deployment across various infrastructures. Enhanced Data Analysis: It optimizes data processing by separating computing and storage. This promotes the development of well-informed business strategies and effective data management. These characteristics provide dependable and easily accessible data to business leaders. Thus, driving informed business strategies and fostering efficient data management. Nasuni Nasuni is a cloud-native file data platform that offers excellent features to enhance an organization’s data analysis capabilities. Efficient Data Management: It enables end-to-end retention of extended metadata, reducing the time spent searching for content. Scalability: It delivers effortless scalability, which increases business productivity within a unified administrative experience. Versatile Integration: It integrates with AWS, enabling customers to build advanced solutions for unstructured data management. Secure Data: It uses native multi-factor authentication to protect data. Enhanced Data Analysis: The Nasuni Analytics Connector allows companies to leverage the strengths of their existing cloud services tools, turning unstructured data into big data. These features guide business leaders to chalk out innovative business approaches while supporting effective data management. OneBlox OneBlox is a powerful solution for cloud data storage management. It offers a suite of features that can significantly enhance an organization’s data analysis capabilities: Efficient Data Management: It uses a comprehensive replication engine and other features. These include Continuous Data Protection (CDP) to protect data and present a unified view of the storage environment. Scalability: It uses a scale-out ring architecture, enabling the global file system to scale from a few TBs to hundreds of TBs without requiring application reconfiguration. Versatile Integration: It integrates seamlessly with backup and recovery offerings from Symantec, Veeam, CommVault, and Unitrends. Secure Data: It provides RAID-less protection against multiple drive failures or multiple node failures by creating three copies of every object for redundancy. Enhanced Data Analysis: It accelerates its object metadata access with a built-in SSD. This helps deliver inline deduplication, continuous data protection, remote replication, and seamless scalability to SMB and NFS-based applications. These features give decision-makers secure, organized, and accessible data to support corporate goals and improve data management. Qlik Replicate Qlik Replicate is a powerful solution for cloud data storage management that can boost an organization’s data analysis capabilities: Efficient Data Ingestion: It provides real-time data replication, ingestion, and streaming via change data capture across various heterogeneous databases, data warehouses, and data lake platforms. Scalability: It is designed to scale and support large-scale enterprise data replication scenarios with a scalable multi-server, multi-task, and multi-threaded architecture. Versatile Integration: It offers swift data loading into numerous data stores or destinations. It also enables easy distribution between endpoints. Secure Data: It uses a “Click-2-Replicate” design that simplifies the replication process by automating the steps required to build a replication solution. Enhanced Data Analysis: Its real-time data integration facilitates data integration between different systems or applications across the organization to ensure that data is consistent and up-to-date. Qlik Replicate’s secure, organized, and accessible data helps decision-makers to drive informed business strategies. Additionally, it promotes efficient data management with an intelligent data analysis tool. Redstor Backup for Microsoft 365 Redstor Backup for Microsoft 365 is a complete solution for cloud data storage management. It can improve an organization’s data analysis capabilities with these features: Efficient Data Management: It allows backing up OneDrive, SharePoint, Exchange, Teams, OneNote, Class and Staff Notebooks data seamlessly from Microsoft to the Redstor cloud. Instant Recovery: Its innovative InstantData technology enables businesses to swiftly resume their operations within minutes by providing instant recovery of any file. Secure Data: It uses advanced AI-powered technology to safeguard Microsoft Office 365 user data. Compliance: It assists customers in complying with the necessary regulations by supporting region-based data processing and storage. Centralized Management: Efficiently manage the protection of all Microsoft Office 365 apps and other Redstor products through a single, intuitive, multi-tenant app. These features let decision-makers grasp secure, organized, and accessible data, to drive innovative business plans and improve data management. StorPool StorPool, a high-performance, software-defined storage system enhances data analysis for organizations: Efficient Data Management: It uses advanced replication and end-to-end data integrity mechanisms, ensuring data reliability and availability. Scalability: Its scale-out architecture allows the global file system to scale from a few TBs to hundreds of TBs without requiring application reconfiguration. Versatile Integration: It integrates seamlessly with various platforms, providing a high-throughput backend for streaming data analytics. Secure Data: It uses a proprietary 64-bit end-to-end data integrity checksum to protect customers’ data. Enhanced Data Analysis: Its real-time data integration ensures data consistency across the organization by integrating systems and applications. These features of one of the top data analysis tools for storage management equip the leaders with reliable and scalable data to drive informed business plans and effective data management. Storj Storj, a decentralized cloud storage solution, offers many benefits for organizations managing cloud data storage and analysis. Enhanced Security: It employs multi-layered encryption and edge-based access management, ensuring maximum privacy and setting a new standard in data security. Superior Performance: Its performance is equivalent to or can exceed that of centralized providers, facilitating rapid global file access. Enterprise SLAs: It provides enterprise-level service-level agreements, ensuring reliable and consistent service. Cost-effective: Its distributed model offers a cost-effective solution for data storage and analysis. Eco-friendly: Its use of spare capacity for data storage makes it a greener alternative to traditional cloud storage. Storj is an ideal recommendation for decision-makers seeking sustainable cloud data storage solutions from the top data management tools. New Technology Trends in Cloud Data Storage Management The future of cloud storage management relies on emerging technological developments. These include the use of multi-cloud and hybrid cloud structures, as well as the rise of NVMe-oF. These trends are transforming the storage and management of data. Comparing the features of tools using a storage management software comparison guide can be helpful. The goal is to get rid of data silos, manage the flood of unstructured data, and balance performance, resilience, efficiency, and simplicity. Keeping up with these upcoming developments in storage management trends is important for successfully managing storage while dramatically saving costs.

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What Is Cloud-Native and Why Does it Matter for CI

Article | February 11, 2020

Continuous intelligence (CI) relies on the real-time analysis of streaming data to produce actionable insights in milliseconds to seconds. Such capabilities have applications throughout a business. In today’s dynamic marketplace, new CI applications that use data from various sources at any given time might be needed on very short notice.The challenge is how to have the flexibility to rapidly develop and deploy new CI applications to meet fast-changing business requirements. A common approach employed today is to use a dynamic architecture that delivers access to data, processing power, and analytics capabilities on demand. In the future, solutions also will likely incorporate artificial intelligence applications to complement the benefits of traditional analytics. Increasingly, cloud-native is the architecture of choice to build and deploy AI-embedded CI applications. A cloud-native approach offers benefits to both the business and developers. Cloud-native applications or services are loosely coupled with explicitly described dependencies.

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Spotlight

Enlighted Inc

Designed to change everything, we started by providing the world’s most advanced IoT platform to Fortune 500 companies around the globe from the heart of Silicon Valley. Now with Siemens as a global partner, our mission is to continue to drive innovation with our 5th-generation smart sensor and innovative app-based technology.

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Cloud Security

Lacework Announces Enterprise Multicloud Platform Updates

PR Newswire | October 25, 2023

Lacework, the data-driven cloud security company, today announced a series of updates that expand the platform's enterprise-grade capabilities to help customers do more in the cloud, securely. Lacework is extending its platform support to new cloud providers in order to give customers more choice as they secure their multicloud environments, adding integrations into leading project management tools to increase operational efficiency around risk management, and enhancing agentless workload scanning, among other updates. Expanded Enterprise Multicloud Support Enterprises implement multicloud strategies for various economic, technical, and legal reasons, and Lacework is committed to supporting its customers' cloud or clouds of choice. Lacework has extended cloud security posture management to Oracle Cloud Infrastructure (OCI), giving teams visibility into their OCI resources and their associated risks. Whether enterprises are using Amazon Web Services, Google Cloud, Azure, OCI or a combination, the unified Lacework platform gives them visibility from a single location, resulting in better context, better outcomes, and faster investigations. We are excited that Lacework has added support for Oracle Cloud Infrastructure. It gives us the opportunity to utilize Cloud Security Posture Management capabilities across our multicloud environment with a single platform, said Karen Prichard, Managing Director Group Security, Liberty Global. Our team can continue to reduce our risk and address our threats quicker with the added visibility and context provided by this new integration. Additionally, the Lacework platform is expanding its industry-leading attack path analysis to Google Cloud and Azure. Attack path analysis from Lacework allows security teams to see their cloud environment through the eyes of an attacker, identifying targets and mapping out how each threat could be exploited to breach a cloud environment. Now Lacework customers leveraging Google Cloud or Azure can gain attack path analysis that is bespoke to each cloud's unique environment. "My colleague already had the chance to identify configuration issues, it immediately flagged something we had to look at — giving us the opportunity to fix it," Simen Kildahl Eriksen, Security Engineer at Cognite, shares. "It provides an invaluable means of identifying potential configuration problems before they escalate into more significant security breaches." In the cloud, organizations routinely create and tear down services and containers quickly in order to meet changing demands. Whether testing-development or running batch jobs, ephemeral workloads and containers are opportunities for bad actors to gain access. It's important that security teams do not lose sight of these short-lived instances. To meet this growing need, Lacework agentless workload scanning has been upgraded to check customer workloads every five minutes for new instances. This granular visibility of what is running and its associated risk assures teams that they have comprehensive visibility into rapidly changing environments and gives confidence that short-lived instances are not falling through the security cracks. Operationalized Risk Management with ServiceNow and Jira Integrations It's not enough for an organization to have a list of vulnerabilities, they need to be able to quickly fix them. To enhance its industry-leading threat visibility tools, the Lacework platform now features integrations with ServiceNow and Jira that improve the process of mitigating vulnerabilities. Now, security and development teams have the premium vulnerability feeds with all the context Lacework is known for integrated into their ticketing system of choice. By connecting these systems to streamline response efforts, the appropriate teams can move faster when securing vulnerabilities. "With the rise of cloud adoption and migration, securing the enterprise has never been more important for organizations," said Deepak Kolingivadi, Head of Security Products at ServiceNow. "The Lacework integration with ServiceNow Vulnerability Response enables our enterprise customers to streamline their response processes by simplifying assignment, collaboration, and remediation of critical vulnerabilities. Using business context in ServiceNow, customers can detect and report the security posture of IT and application environments within the Now Platform. We look forward to continuing our partnership with Lacework and helping mutual customers address cybersecurity threats more quickly and efficiently." Lacework's integration with ServiceNow Vulnerability Response offerings for infrastructure and container applications is currently available in the ServiceNow marketplace. Lacework's integration to Security in Jira is in private preview. About Lacework Lacework keeps organizations secure in the cloud, allowing them to innovate faster with confidence. Cloud security requires a fundamentally new approach and the Lacework platform is designed to scale with the volume, variety, and velocity of cloud data across an organization's cloud environment: code, identities, containers, and multi-cloud infrastructure. Only Lacework provides Security and Development teams with a correlated and prioritized end-to-end view that pinpoints the largest risks and handful of security events that matter most. Learn more at www.lacework.com.

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Cloud App Management

Webscale Acquires Section.io to Launch CloudFlow: An AI-Based Platform For Smart Distributed Computing and Cloud Cost Control

GlobeNewswire | October 20, 2023

Webscale, the industry leader in Intelligent CloudOps, proudly announces its acquisition of Section.io, a trailblazer in edge-native computing. This strategic acquisition has paved the way for the launch of CloudFlow, a revolutionary Kubernetes orchestration platform with patented Artificial Intelligence (AI) and Machine Learning (ML) automation at its core. This unprecedented level of smart automation allows organizations to take a zero-ops approach to enhancing operational efficiency, optimizing compute resources, and delivering ultra low-latency performance. In today's economic landscape, where organizations face the constant challenge of balancing cloud cost optimization and surging compute demands driven by increasing user experience expectations, Webscale is pioneering a new course. CloudFlow empowers businesses, from Independent Software Vendors (ISVs) to enterprise organizations, to harness the full potential of AI to drive deep levels of efficiency into their distributed cloud computing strategies. Key Features of CloudFlow: AI-driven Adaptive Edge Engine: CloudFlow enlists patented AI/ML capabilities to ensure efficient resource allocation, dynamic scaling, and cost optimization, reducing cloud infrastructure costs while maximizing performance. One-click Multi-cloud: CloudFlow’s Composable Edge Cloud (CEC) enables one-click multi-cloud integration, allowing users to operate seamlessly across various cloud providers, liberating them from vendor lock-in and providing unparalleled least cost routing. Dynamic Cost Management: CloudFlow continuously monitors all environments, adjusting resource allocation and cluster size in real-time through coordination with Endpoint Controller, HPA, VPA, and HCA. This ensures judicious resource usage, resulting in cost savings without performance compromise. Ironclad Security: The CloudFlow platform is SOC2 Type II, PCI-DSS and HIPAA compliant, ensuring the safety of your customers’ personal and financial data. Zero-Ops Simplicity: By utilizing CloudFlow, zero-ops distributed cloud computing becomes an immediate reality, saving organizations time, effort, and resources. A Seamless Collaboration The acquisition of Section.io by Webscale signifies a pivotal moment in cloud-native computing, said Gary Schofield, CEO of Webscale. Our shared vision led us to create CloudFlow, a platform designed to simplify Kubernetes operations while using AI to efficiently manage workload placement and resource allocation across our clients’ networks. It's a game-changer for businesses seeking control over their margins by keeping inflated cloud infrastructure costs in check without sacrificing performance or security posture. Gary added, "CloudFlow embodies the essence of innovation and is set to revolutionize cloud-agnostic operations for our customers across diverse sectors, including e-commerce, digital experience, ISVs, and enterprises." Former Section.io CTO, Dan Bartholomew, has embarked on an exciting journey as Chief Product Officer within the expansive Webscale organization. In his new role, Dan is leading the Product Development organization, steering the innovation and integration roadmap of cutting-edge technology solutions from Section and Webscale. Under the united Webscale banner, we're poised to redefine the future of digital experiences, setting new standards for smart distributed computing and cloud infrastructure cost control. CloudFlow represents a significant milestone in the cloud edge-native computing landscape. To explore how CloudFlow's AI-based technology can transform your cloud operations, visit www.webscale.com. About Webscale At Webscale, we understand the evolving cloud technology landscape and the challenges that organizations face in harnessing its full potential. That's why we've embarked on a mission to provide ecommerce businesses, digital experience providers, and SaaS vendors AI-rich tooling through our revolutionary CloudFlow platform, powered by the recent acquisition of Section.io. CloudFlow enables businesses to inject intelligence into their Kubernetes operations like never before and reimagine their distributed computing and cloud cost optimization strategies. We believe that intelligence is the future of cloud computing, and CloudFlow represents our vision to empower organizations with the tools they need to thrive in the digital age. The CloudFlow platform has been designed to deeply integrate AI into multiple aspects of cloud management, from optimizing resource allocation to scaling Kubernetes architecture efficiently to meet minute-by-minute demand.

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Cloud Deployment Models

Mirantis’ Lens AppIQ: Upgrading Kubernetes Application Management

Mirantis | September 22, 2023

Mirantis has introduced Lens AppIQ, a new tool designed to simplify Kubernetes application management. Available directly to the 50,000 organizations using Lens, Lens AppIQ offers application intelligence, making it accessible for non-Kubernetes specialists to oversee applications across multiple clusters. Lens AppIQ aggregates information from various configuration files and sources, presenting it in a user-friendly tabbed display. This feature allows cloud-native developers to streamline the deployment and management of Kubernetes applications, offering web-based tools for viewing application details, configuring security measures, and automating deployment processes. With a quick launch time of under a minute, Lens AppIQ swiftly identifies applications in connected clusters and maps their components. Developers can access application architecture, metadata, logs, events, and more through Lens Desktop’s new 'Applications' view or the Lens AppIQ web portal, simplifying debugging, accelerating code releases, and enhancing performance optimization. DevOps professionals, platform engineers, and operators can utilize Lens AppIQ to define, monitor, and enforce policies related to application performance, security, and compliance. Automation features in Lens AppIQ facilitate repeatable deployments and enable effortless application migration to new Kubernetes environments. Miska Kaipiainen, Vice President of Engineering at Mirantis, reportedly stated, While Lens Desktop already provides an incredibly user-friendly experience for Kubernetes management, we understand that cloud-native development doesn't end there. That's why we've created Lens AppIQ. Lens AppIQ complements Lens Desktop by offering real-time intelligence and additional insights into the apps running on your Kubernetes clusters. This not only makes debugging, operation, and security easier but also opens up Kubernetes to a broader audience of developers who can benefit from streamlined processes without having to become Kubernetes experts. [Source – Businesswire] Lens AppIQ is available for free for small-scale and trial use, accommodating up to 10 nodes, two clusters, and two users. A Pro plan is available for larger-scale use, supporting up to 100 nodes, 10 clusters, and 50 users, priced at $35 per node monthly, inclusive of 8 hours/5-day business hours support. Enterprises can opt for a bespoke version with 24/7 support and custom pricing. Lens AppIQ is accessible within Lens Desktop for the 50,000 organizations currently using Lens and is also available as a Software as a Service (SaaS) solution. About Lens With over 1 million users worldwide, Lens Desktop is a leading tool for boosting productivity in Kubernetes application development and management. This desktop application breaks down barriers for newcomers to Kubernetes while significantly enhancing the efficiency of experienced users. Lens supports all certified Kubernetes distributions on any infrastructure and seamlessly runs on Linux, macOS, and Windows. As the world's largest and most advanced Kubernetes platform, it provides real-time workload management, development, debugging, monitoring, and troubleshooting across multiple clusters. Built on open-source principles, Lens enjoys a strong community with over 20,000 stars on GitHub. About Mirantis Mirantis is a leading company streamlining code delivery on public and private clouds with a ZeroOps approach to Kubernetes. It serves global enterprises, enhancing developer productivity and offering secure cloud solutions. Its clients include Adobe, DocuSign, PayPal, and others across diverse industries. Mirantis contributes to open-source projects like Lens and Kubernetes, empowering businesses to tackle complex challenges.

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Cloud Security

Lacework Announces Enterprise Multicloud Platform Updates

PR Newswire | October 25, 2023

Lacework, the data-driven cloud security company, today announced a series of updates that expand the platform's enterprise-grade capabilities to help customers do more in the cloud, securely. Lacework is extending its platform support to new cloud providers in order to give customers more choice as they secure their multicloud environments, adding integrations into leading project management tools to increase operational efficiency around risk management, and enhancing agentless workload scanning, among other updates. Expanded Enterprise Multicloud Support Enterprises implement multicloud strategies for various economic, technical, and legal reasons, and Lacework is committed to supporting its customers' cloud or clouds of choice. Lacework has extended cloud security posture management to Oracle Cloud Infrastructure (OCI), giving teams visibility into their OCI resources and their associated risks. Whether enterprises are using Amazon Web Services, Google Cloud, Azure, OCI or a combination, the unified Lacework platform gives them visibility from a single location, resulting in better context, better outcomes, and faster investigations. We are excited that Lacework has added support for Oracle Cloud Infrastructure. It gives us the opportunity to utilize Cloud Security Posture Management capabilities across our multicloud environment with a single platform, said Karen Prichard, Managing Director Group Security, Liberty Global. Our team can continue to reduce our risk and address our threats quicker with the added visibility and context provided by this new integration. Additionally, the Lacework platform is expanding its industry-leading attack path analysis to Google Cloud and Azure. Attack path analysis from Lacework allows security teams to see their cloud environment through the eyes of an attacker, identifying targets and mapping out how each threat could be exploited to breach a cloud environment. Now Lacework customers leveraging Google Cloud or Azure can gain attack path analysis that is bespoke to each cloud's unique environment. "My colleague already had the chance to identify configuration issues, it immediately flagged something we had to look at — giving us the opportunity to fix it," Simen Kildahl Eriksen, Security Engineer at Cognite, shares. "It provides an invaluable means of identifying potential configuration problems before they escalate into more significant security breaches." In the cloud, organizations routinely create and tear down services and containers quickly in order to meet changing demands. Whether testing-development or running batch jobs, ephemeral workloads and containers are opportunities for bad actors to gain access. It's important that security teams do not lose sight of these short-lived instances. To meet this growing need, Lacework agentless workload scanning has been upgraded to check customer workloads every five minutes for new instances. This granular visibility of what is running and its associated risk assures teams that they have comprehensive visibility into rapidly changing environments and gives confidence that short-lived instances are not falling through the security cracks. Operationalized Risk Management with ServiceNow and Jira Integrations It's not enough for an organization to have a list of vulnerabilities, they need to be able to quickly fix them. To enhance its industry-leading threat visibility tools, the Lacework platform now features integrations with ServiceNow and Jira that improve the process of mitigating vulnerabilities. Now, security and development teams have the premium vulnerability feeds with all the context Lacework is known for integrated into their ticketing system of choice. By connecting these systems to streamline response efforts, the appropriate teams can move faster when securing vulnerabilities. "With the rise of cloud adoption and migration, securing the enterprise has never been more important for organizations," said Deepak Kolingivadi, Head of Security Products at ServiceNow. "The Lacework integration with ServiceNow Vulnerability Response enables our enterprise customers to streamline their response processes by simplifying assignment, collaboration, and remediation of critical vulnerabilities. Using business context in ServiceNow, customers can detect and report the security posture of IT and application environments within the Now Platform. We look forward to continuing our partnership with Lacework and helping mutual customers address cybersecurity threats more quickly and efficiently." Lacework's integration with ServiceNow Vulnerability Response offerings for infrastructure and container applications is currently available in the ServiceNow marketplace. Lacework's integration to Security in Jira is in private preview. About Lacework Lacework keeps organizations secure in the cloud, allowing them to innovate faster with confidence. Cloud security requires a fundamentally new approach and the Lacework platform is designed to scale with the volume, variety, and velocity of cloud data across an organization's cloud environment: code, identities, containers, and multi-cloud infrastructure. Only Lacework provides Security and Development teams with a correlated and prioritized end-to-end view that pinpoints the largest risks and handful of security events that matter most. Learn more at www.lacework.com.

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Cloud App Management

Webscale Acquires Section.io to Launch CloudFlow: An AI-Based Platform For Smart Distributed Computing and Cloud Cost Control

GlobeNewswire | October 20, 2023

Webscale, the industry leader in Intelligent CloudOps, proudly announces its acquisition of Section.io, a trailblazer in edge-native computing. This strategic acquisition has paved the way for the launch of CloudFlow, a revolutionary Kubernetes orchestration platform with patented Artificial Intelligence (AI) and Machine Learning (ML) automation at its core. This unprecedented level of smart automation allows organizations to take a zero-ops approach to enhancing operational efficiency, optimizing compute resources, and delivering ultra low-latency performance. In today's economic landscape, where organizations face the constant challenge of balancing cloud cost optimization and surging compute demands driven by increasing user experience expectations, Webscale is pioneering a new course. CloudFlow empowers businesses, from Independent Software Vendors (ISVs) to enterprise organizations, to harness the full potential of AI to drive deep levels of efficiency into their distributed cloud computing strategies. Key Features of CloudFlow: AI-driven Adaptive Edge Engine: CloudFlow enlists patented AI/ML capabilities to ensure efficient resource allocation, dynamic scaling, and cost optimization, reducing cloud infrastructure costs while maximizing performance. One-click Multi-cloud: CloudFlow’s Composable Edge Cloud (CEC) enables one-click multi-cloud integration, allowing users to operate seamlessly across various cloud providers, liberating them from vendor lock-in and providing unparalleled least cost routing. Dynamic Cost Management: CloudFlow continuously monitors all environments, adjusting resource allocation and cluster size in real-time through coordination with Endpoint Controller, HPA, VPA, and HCA. This ensures judicious resource usage, resulting in cost savings without performance compromise. Ironclad Security: The CloudFlow platform is SOC2 Type II, PCI-DSS and HIPAA compliant, ensuring the safety of your customers’ personal and financial data. Zero-Ops Simplicity: By utilizing CloudFlow, zero-ops distributed cloud computing becomes an immediate reality, saving organizations time, effort, and resources. A Seamless Collaboration The acquisition of Section.io by Webscale signifies a pivotal moment in cloud-native computing, said Gary Schofield, CEO of Webscale. Our shared vision led us to create CloudFlow, a platform designed to simplify Kubernetes operations while using AI to efficiently manage workload placement and resource allocation across our clients’ networks. It's a game-changer for businesses seeking control over their margins by keeping inflated cloud infrastructure costs in check without sacrificing performance or security posture. Gary added, "CloudFlow embodies the essence of innovation and is set to revolutionize cloud-agnostic operations for our customers across diverse sectors, including e-commerce, digital experience, ISVs, and enterprises." Former Section.io CTO, Dan Bartholomew, has embarked on an exciting journey as Chief Product Officer within the expansive Webscale organization. In his new role, Dan is leading the Product Development organization, steering the innovation and integration roadmap of cutting-edge technology solutions from Section and Webscale. Under the united Webscale banner, we're poised to redefine the future of digital experiences, setting new standards for smart distributed computing and cloud infrastructure cost control. CloudFlow represents a significant milestone in the cloud edge-native computing landscape. To explore how CloudFlow's AI-based technology can transform your cloud operations, visit www.webscale.com. About Webscale At Webscale, we understand the evolving cloud technology landscape and the challenges that organizations face in harnessing its full potential. That's why we've embarked on a mission to provide ecommerce businesses, digital experience providers, and SaaS vendors AI-rich tooling through our revolutionary CloudFlow platform, powered by the recent acquisition of Section.io. CloudFlow enables businesses to inject intelligence into their Kubernetes operations like never before and reimagine their distributed computing and cloud cost optimization strategies. We believe that intelligence is the future of cloud computing, and CloudFlow represents our vision to empower organizations with the tools they need to thrive in the digital age. The CloudFlow platform has been designed to deeply integrate AI into multiple aspects of cloud management, from optimizing resource allocation to scaling Kubernetes architecture efficiently to meet minute-by-minute demand.

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Cloud Deployment Models

Mirantis’ Lens AppIQ: Upgrading Kubernetes Application Management

Mirantis | September 22, 2023

Mirantis has introduced Lens AppIQ, a new tool designed to simplify Kubernetes application management. Available directly to the 50,000 organizations using Lens, Lens AppIQ offers application intelligence, making it accessible for non-Kubernetes specialists to oversee applications across multiple clusters. Lens AppIQ aggregates information from various configuration files and sources, presenting it in a user-friendly tabbed display. This feature allows cloud-native developers to streamline the deployment and management of Kubernetes applications, offering web-based tools for viewing application details, configuring security measures, and automating deployment processes. With a quick launch time of under a minute, Lens AppIQ swiftly identifies applications in connected clusters and maps their components. Developers can access application architecture, metadata, logs, events, and more through Lens Desktop’s new 'Applications' view or the Lens AppIQ web portal, simplifying debugging, accelerating code releases, and enhancing performance optimization. DevOps professionals, platform engineers, and operators can utilize Lens AppIQ to define, monitor, and enforce policies related to application performance, security, and compliance. Automation features in Lens AppIQ facilitate repeatable deployments and enable effortless application migration to new Kubernetes environments. Miska Kaipiainen, Vice President of Engineering at Mirantis, reportedly stated, While Lens Desktop already provides an incredibly user-friendly experience for Kubernetes management, we understand that cloud-native development doesn't end there. That's why we've created Lens AppIQ. Lens AppIQ complements Lens Desktop by offering real-time intelligence and additional insights into the apps running on your Kubernetes clusters. This not only makes debugging, operation, and security easier but also opens up Kubernetes to a broader audience of developers who can benefit from streamlined processes without having to become Kubernetes experts. [Source – Businesswire] Lens AppIQ is available for free for small-scale and trial use, accommodating up to 10 nodes, two clusters, and two users. A Pro plan is available for larger-scale use, supporting up to 100 nodes, 10 clusters, and 50 users, priced at $35 per node monthly, inclusive of 8 hours/5-day business hours support. Enterprises can opt for a bespoke version with 24/7 support and custom pricing. Lens AppIQ is accessible within Lens Desktop for the 50,000 organizations currently using Lens and is also available as a Software as a Service (SaaS) solution. About Lens With over 1 million users worldwide, Lens Desktop is a leading tool for boosting productivity in Kubernetes application development and management. This desktop application breaks down barriers for newcomers to Kubernetes while significantly enhancing the efficiency of experienced users. Lens supports all certified Kubernetes distributions on any infrastructure and seamlessly runs on Linux, macOS, and Windows. As the world's largest and most advanced Kubernetes platform, it provides real-time workload management, development, debugging, monitoring, and troubleshooting across multiple clusters. Built on open-source principles, Lens enjoys a strong community with over 20,000 stars on GitHub. About Mirantis Mirantis is a leading company streamlining code delivery on public and private clouds with a ZeroOps approach to Kubernetes. It serves global enterprises, enhancing developer productivity and offering secure cloud solutions. Its clients include Adobe, DocuSign, PayPal, and others across diverse industries. Mirantis contributes to open-source projects like Lens and Kubernetes, empowering businesses to tackle complex challenges.

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Events