There was a time when the cloud was seen mainly as a storage and disaster recovery option. Cloud services providers were engaged in a race to the bottom to lower their rack space prices. Some vendors added load balancers, databases, and monitoring to their service portfolios to achieve differentiation from colocation service and data center providers.
However, in the early 2000s, virtualization started upending the market, providing businesses with higher flexibility and efficiency to harness cloud resources. Today, container technology is again bringing a similar market shift by significantly reducing the overheads associated with cloud-hosted applications.
In the transition, Kubernetes has become the de-facto standard for deploying and orchestrating containerized applications.
A primary advantage of containerization is that it allows applications to run reliably across different infrastructures as it packages the software and all its dependencies (runtime, system tools, system libraries, settings, etc.) together. It means enterprises have increased flexibility to move their applications around (e.g., from one cloud to another).
Containers also add agility to development as developers can frequently push code to production in smaller increments, reducing the chances of big failures. They can easily roll back an application to a previous stable version to minimize losses and make changes as per the customer feedback. Further, containers make deployments faster as it is possible to build images automatically at the time of build/release and deploy them as atomic units.
Deploying lightweight containers is significantly quicker as compared to legacy monolithic deployments. Moreover, developers can choose between rolling, blue-green, and canary deployments for effective release management. Another major advantage for development teams is that containerization helps them build and share code quickly in the form of microservices.
Containers also provide an edge over virtual machines (VMs) in terms of scalability; it takes only a few seconds to start a container while provisioning a VM takes up more time. Last but not least, containerized applications can lower operational costs significantly by providing optimal utilization of resources.
While businesses want to jump on the bandwagon and have made significant investments in refactoring their applications, monitoring and managing containerized applications is still a major challenge.
Containerization brings a paradigm shift to software development and has a steep learning curve for the DevOps team. To free developers from learning a new technology, a lot of enterprises have dedicated teams that write docker files and deployment manifests so that development teams can focus on writing the code.
However, developers are now playing a more crucial role beyond writing and committing code. They have increased responsibility for ensuring stable operations in production. It means they need to quickly understand the intricacies of different containerization platforms, learn how to set up and manage Kubernetes clusters, deploy tools for image scanning, etc., and find newer ways to ensure compliance and security across the development lifecycle.
It becomes difficult for enterprise teams to identify the right tools and technologies amidst the rapidly evolving container ecosystem.
They need to evaluate several options, including on-premises Kubernetes solutions, managed services by cloud service providers, service discovery tools, networking and security management suites, application performance management (APM) tools, observability/monitoring tools, and more.
It is not always easy to gauge the ROI or get clear visibility into the costs of such commercial tools/solutions in the evaluation stages.
Enterprises often lack the right strategy for implementation, and most containerization initiatives are only ad-hoc in nature. As a result, development, operations, and other teams have different visions, priorities, and objectives for containerization, leading to a lack of coordination and inefficient transition. It is seen that teams track different metrics without proper benchmarking and fail to assess the direction and progress of their implementation accurately.
While containers offer the opportunity to reduce operational costs, many organizations are unable to make the most of their investments. They lack the proper tools and expertise to monitor orchestrated container environments.
Traditional monitoring tools and techniques are ineffective in container environments which include multiple components such as pods, nodes, services, and more. Organizations are often unable to find tools and systems that enable continuous collection and analysis of observability data from all components.
Enterprise teams are often dealing with multiple versions of applications in the same cluster as per their deployment approach, which means they need to keep track of different resources. Kubernetes has a wide attack surface consisting of infra, OS, network, application, platform, etc., with each component having its own security risks.
In such a scenario, security oversights become more likely as developers and operations teams lack real-time data and visibility into potential vulnerabilities. Further, as developers are often overworked resolving a myriad of challenges in the initial stages of their containerization journey, they often lose track of security and compliance.
How to overcome these challenges and make the most of your technology investments? Stay tuned for part 2 of this blog to find your answers.