Open source tools are no longer frowned upon as cheap alternatives to proprietary tools. In fact, they've now become the engine that powers the modern containerization movement that's sweeping across application development. Today, let's take a look at the top three open source tools that are essential to building containerized apps.
Kubernetes is a container orchestration tool that simplifies the management of thousands of containers in production. It acts as a layer that separates containerized apps from the underlying infrastructure. In this way, it can facilitate operations across multiple clouds and data centers. Kubernetes' strengths are many, but most essential are its automated handling of failover and load balancing. As new pods (groups of containers) are added, the workload is balanced across all pods automatically. Additionally, if any pod fails or is compromised, Kubernetes ensures a replica pod can replace it. Kubernetes is making containers a reality in real-world use cases across companies large and small.
Elasticsearch is a distributed full-text database that makes it easy to analyze large quantities of data in real time. As the central part of the Elastic Stack, Elasticsearch has gained widespread adoption across a range of use cases, like monitoring, e-commerce product search, log analysis and recommendation engines. Many organizations use Elasticsearch as part of their container toolkit for analyzing the heaps of performance and monitoring data that containerized apps churn out. With the thousands of containers running in a typical production environment, the amount of data they generate needs to be analyzed in real time. Elasticsearch is the perfect tool for this job. In fact, many paid tools are based off of Elasticsearch, making it not just a tool, but a platform on which other tools are built. Kubernetes has a native integration with Elasticsearch to which it can send all log data.
Monitoring is critical to successfully running containerized apps in production. The leading open source container monitoring tool today is Prometheus. It is especially well-suited for analyzing time-series data in real time. Prometheus lets you label every stream of time-series data that flows in and lets you create temporary labels for any data that results from a query you run. With a powerful query language, PromQL, Prometheus lets you quickly derive insight from your data. It has its own visualization options, but for more advanced visualizations, you can easily route Prometheus data to a visualization tool like Grafana.
As you move from virtual machines to containers to run much of your application workloads, you need a new breed of tools to manage these containers in production. Other worthy tools that were not included in this post but deserve mention are gRPC, Fluentd and Istio. However, for the impact they are having, Kubernetes, Elasticsearch and Prometheus are the top three open source tools that enable running containerized applications at scale.
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