Coverity Scan vs Kubernetes: What are the differences?
Developers describe Coverity Scan as "Find and fix defects in your Java, C/C++ or C# open source project for free". Coverity's implementation of static analysis can follow all the possible paths of execution through source code (including interprocedurally) and find defects and vulnerabilities caused by the conjunction of statements that are not errors independent of each other. On the other hand, Kubernetes is detailed as "Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops". Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.
Coverity Scan can be classified as a tool in the "Code Review" category, while Kubernetes is grouped under "Container Tools".
Some of the features offered by Coverity Scan are:
- Test every line of code and potential execution path.
- The root cause of each defect is clearly explained, making it easy to fix bugs
- Integrates with GitHub and Travis CI
On the other hand, Kubernetes provides the following key features:
- Lightweight, simple and accessible
- Built for a multi-cloud world, public, private or hybrid
- Highly modular, designed so that all of its components are easily swappable
Kubernetes is an open source tool with 55.1K GitHub stars and 19.1K GitHub forks. Here's a link to Kubernetes's open source repository on GitHub.
Our whole DevOps stack consists of the following tools:
- GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
- Respectively Git as revision control system
- SourceTree as Git GUI
- Visual Studio Code as IDE
- CircleCI for continuous integration (automatize development process)
- Prettier / TSLint / ESLint as code linter
- SonarQube as quality gate
- Docker as container management (incl. Docker Compose for multi-container application management)
- VirtualBox for operating system simulation tests
- Kubernetes as cluster management for docker containers
- Heroku for deploying in test environments
- nginx as web server (preferably used as facade server in production environment)
- SSLMate (using OpenSSL) for certificate management
- Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
- PostgreSQL as preferred database system
- Redis as preferred in-memory database/store (great for caching)
The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:
- Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
- Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
- Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
- Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
- Scalability: All-in-one framework for distributed systems.
- Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
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