Kong is a cloud-native, fast, scalable, and distributed Microservice Abstraction Layer (also known as an API Gateway, API Middleware or in some cases Service Mesh). Backed by the battle-tested NGINX with a focus on high performance, Kong was made available as an open-source platform in 2015. Under active development, Kong is used in production at thousands of organizations from startups, Global 5000 and Government organizations.
 
If you are building for web, mobile or IoT (Internet of Things) you will likely end up needing common functionality to run your actual software. Kong can help by acting as a gateway (or a sidecar) for microservices requests while providing load balancing, logging, authentication, rate-limiting and more through plugins.
 
Its features include: 
<ul>
<li>Cloud-Native: Platform agnostic, Kong can run from bare metal to
Kubernetes.</li>
<li>Dynamic Load Balancing: Load balance traffic across multiple backend
services.</li>
<li>Service Discovery: Resolve SRV records in third-party DNS resolvers like
Consul.</li>
<li>Serverless: Invoke and secure AWS Lambda or OpenWhisk fuctions directly
from Kong.</li>
<li>WebSockets: Communicate to your upstream services via WebSockets.</li>
<li>OAuth2.0: Easily add OAuth2.0 authentication to your APIs.</li>
<li>Logging: Log requests and responses to your system over HTTP, TCP, UDP,
or to disk.</li>
<li>Security: ACL, Bot detection, whitelist/blacklist IPs, etc...</li>
<li>Syslog: Logging to System log.</li>
<li>SSL: Setup a Specific SSL Certificate for an underlying service or API.</li>
<li>Monitoring: Live monitoring provides key load and performance server
metrics.</li>
<li>Authentications: HMAC, JWT, Basic, and more.</li>
<li>Rate-limiting: Block and throttle requests based on many variables.</li>
<li>Transformations: Add, remove, or manipulate HTTP requests and responses.</li>
<li>Caching: Cache and serve responses at the proxy layer.</li>
<li>CLI: Control your Kong cluster from the command line.</li>
<li>REST API: Kong can be operated with its RESTful API for maximum
flexibility.</li>
<li>Geo-Replicated: Configs are always up-to-date across different regions.</li>
<li>Failure Detection &amp; Recovery: Kong is unaffected if one of your Cassandra
nodes goes down.</li>
<li>Clustering: All Kong nodes auto-join the cluster keeping their config
updated across nodes.</li>
<li>Scalability: Distributed by nature, Kong scales horizontally by simply
adding nodes.</li>
<li>Performance: Kong handles load with ease by scaling and using NGINX at
the core.</li>
<li>Plugins: Extendable architecture for adding functionality to Kong and
APIs.</li>
</ul>

Kong is a cloud-native, fast, scalable, and distributed Microservice Abstraction Layer (also known as an API Gateway, API Middleware or in some cases Service Mesh). Backed by the battle-tested NGINX with a focus on high performance, Kong was made available as an open-source platform in 2015. Under active development, Kong is used in production at thousands of organizations from startups, Global 5000 and Government organizations.

Kong - The Microservice API Gateway 

Mist is an open source platform for managing heterogeneous computing infrastructure, aka a Multi-Cloud Management Platform. The managed computing resources may be running on any combination of public clouds, private clouds, hypervisors, bare metal servers, container hosts. Mist provides a unified way to operate, monitor & govern cloud resources. The mission statement of the Mist platform is to help commoditize computing by alleviating vendor lock-in.

 Mist - Open source multi-cloud management platform

StackStorm is a platform for integration and automation across services and tools. It ties together your existing infrastructure and application environment so you can more easily automate that environment - with a particular focus on taking actions in response to events. StackStorm (aka "IFTTT for Ops") is event-driven automation for auto-remediation, security responses, troubleshooting, deployments, and more. Includes rules engine, workflow, 160 integration packs with 6000+ actions

StackStorm - Connects all your apps, services, and workflows.

Pyroscope is an open source continuous profiling platform. It will help you Find performance issues in your code, Resolve issues with high CPU utilization, Understand the call tree of your application, Track changes over time. It can store years of profiling data from multiple applications. You can look at years of data at a time or zoom in on specific events. 

Pyroscope - Open Source Continuous Profiling Platform


Bytebase is a web-based, zero-config, dependency-free database schema change and version control management tool for developers and DBAs. It is for developers to collaborate on database schemas changes. It helps to construct a single pipeline to propagate the schema change across multiple environments. It can also store the schemas in VCS and trigger a new pipeline upon commit push. 
 
Developers first submit their SQL statement for DBA to review. After review is approved, the SQL statement will then be applied to the corresponding database. "Version controlled schema" aka "Database-as-code" is a practice to store the database schema in a version control system (VCS) just like how application code is stored. The database schema consists of a bunch of database migration scripts.

Bytebase is a web-based, zero-config, dependency-free database schema change and version control management tool for developers and DBAs. It is for developers to collaborate on database schemas changes. It helps to construct a single pipeline to propagate the schema change across multiple environments. It can also store the schemas in VCS and trigger a new pipeline upon commit push. 

ByteBase - Web-based, zero-config, dependency-free database schema change and version control tool for teams

OpenEBS is containerized block storage written in Go for cloud native and other environments w/ per container (or pod) QoS SLAs, tiering and replica policies across AZs and environments, and predictable and scalable performance.
 
OpenEBS allows you to treat your persistent workload containers, such as DBs on containers, just like other containers. OpenEBS itself is deployed as just another container on your host, and enables storage services that can be designated on a per pod, application, cluster or container level, including:
<ul>
<li>Data persistence across nodes, dramatically reducing time spent rebuilding Cassandra rings for example</li>
<li>Synchronization of data across availability zones and cloud providers</li>
<li>Use of commodity hardware plus a container engine to deliver seriously scale out block storage</li>
<li>Integration with orchestrators, so that developer and application intent flows into OpenEBS configurations automatically</li>
<li>Management of tiering to and from S3 and other targets</li>
<li>Plus we are bringing our experience from BSD based containerization and delivering QoS for customers from our CloudByte experience over to OpenEBS - expect to see more intelligence and manageability</li>
</ul>

OpenEBS is containerized block storage written in Go for cloud native and other environments w/ per container (or pod) QoS SLAs, tiering and replica policies across AZs and environments, and predictable and scalable performance. 


OpenEBS - Containerized Storage for Containers

The APM Server receives data from APM agents and transforms them into Elasticsearch documents. It does this by exposing an HTTP server endpoint to which agents stream the APM data they collect. After the APM Server has validated and processed events from the APM agents, the server transforms the data into Elasticsearch documents and stores them in corresponding Elasticsearch indices.

Elastic APM Server - Receives data from the Elastic APM agents and stores the data into Elasticsearch

Apache APISIX is a dynamic, real-time, high-performance API gateway. APISIX provides rich traffic management features such as load balancing, dynamic upstream, canary release, circuit breaking, authentication, observability, and more. You can use Apache APISIX to handle traditional north-south traffic, as well as east-west traffic between services. It can also be used as a k8s ingress controller.
 
You can use Apache APISIX as a traffic entrance to process all business data, including dynamic routing, dynamic upstream, dynamic certificates, A/B testing, canary release, blue-green deployment, limit rate, defense against malicious attacks, metrics, monitoring alarms, service observability, service governance, etc.

Apache APISIX is a dynamic, real-time, high-performance API gateway. APISIX provides rich traffic management features such as load balancing, dynamic upstream, canary release, circuit breaking, authentication, observability, and more. You can use Apache APISIX to handle traditional north-south traffic, as well as east-west traffic between services. It can also be used as a k8s ingress controller.

Apache APISIX - Dynamic, real-time, high-performance API gateway

Deepfence ThreatMapper helps you to monitor and secure your running applications, in Cloud, Kubernetes, Docker, and Fargate Serverless. ThreatMapper scans your platforms and identifies pods, containers, applications, and infrastructure. Use ThreatMapper to discover the topology of your applications and attack surface. It obtains manifests of dependencies from running pods and containers, serverless apps, applications, and operating system. ThreatMapper matches these against vulnerability feeds to identify vulnerable components.
 
ThreatMapper discovers, annotates and displays the topology of your applications across multiple cloud environments. It ranks discovered vulnerabilities against CVSS and other severity scores, exploit method and proximity to attack surface, in order to identify which issues pose the greatest risk of exploit.

Deepfence ThreatMapper helps you to monitor and secure your running applications, in Cloud, Kubernetes, Docker, and Fargate Serverless. ThreatMapper scans your platforms and identifies pods, containers, applications, and infrastructure. Use ThreatMapper to discover the topology of your applications and attack surface. It obtains manifests of dependencies from running pods and containers, serverless apps, applications, and operating system. ThreatMapper matches these against vulnerability feeds to identify vulnerable components.

DeepFence - Identify vulnerabilities in running containers, images, hosts and repositories

With watchtower you can update the running version of your containerized app simply by pushing a new image to the Docker Hub or your own image registry. Watchtower will pull down your new image, gracefully shut down your existing container and restart it with the same options that were used when it was deployed initially. 

Watchtower - A process for automating Docker container base image updates

Kubescape is an open-source Kubernetes security platform. It includes risk analysis, security compliance, and misconfiguration scanning. Targeted at the DevSecOps practitioner or platform engineer, it offers an easy-to-use CLI interface, flexible output formats, and automated scanning capabilities. It saves Kubernetes users and admins precious time, effort, and resources.
Kubescape scans clusters, YAML files, and Helm charts. It detects misconfigurations according to multiple frameworks (including&nbsp;<a href="https://www.armosec.io/blog/kubernetes-hardening-guidance-summary-by-armo/?utm_source=github&amp;utm_medium=repository" target="_blank" rel="noopener">NSA-CISA</a>,&nbsp;<a href="https://www.microsoft.com/security/blog/2021/03/23/secure-containerized-environments-with-updated-threat-matrix-for-kubernetes/" target="_blank" rel="noopener">MITRE ATT&amp;CK </a>and the&nbsp;<a href="https://www.armosec.io/blog/cis-kubernetes-benchmark-framework-scanning-tools-comparison/?utm_source=github&amp;utm_medium=repository" target="_blank" rel="noopener">CIS Benchmark</a>).
Kubescape uses&nbsp;<a href="https://github.com/open-policy-agent/opa" target="_blank" rel="noopener">Open Policy Agent</a>&nbsp;to verify Kubernetes objects against&nbsp;<a href="https://github.com/kubescape/regolibrary" target="_blank" rel="noopener">a library of posture controls</a>. By default, the results are printed in a console but they can be exported to JSON and PDF.
Kubescape is running the following tests according to what is defined by Kubernetes Hardening Guidance by NSA and CISA.
<ul>
<li>Non-root containers</li>
<li>Immutable container filesystem</li>
<li>Privileged containers</li>
<li>hostPID, hostIPC privileges</li>
<li>hostNetwork access</li>
<li>allowedHostPaths field</li>
<li>Protecting pod service account tokens</li>
<li>Resource policies</li>
<li>Control plane hardening</li>
<li>Exposed dashboard</li>
<li>Allow privilege escalation</li>
<li>Applications credentials in configuration files</li>
<li>Cluster-admin binding</li>
<li>Exec into container</li>
<li>Dangerous capabilities</li>
<li>Insecure capabilities</li>
<li>Linux hardening</li>
</ul>

An open-source Kubernetes security platform for your IDE, CI/CD pipelines, and clusters.



Kubescape - An open-source Kubernetes security platform for your IDE, CI/CD pipelines, and clusters

Kubernetes has made it very easy to deploy applications to the cloud at a higher scale than ever, but the development practices have not evolved at the same speed as application deployment patterns. Today, most developers try to either run parts of the infrastructure locally, or just test these integrations directly in the cluster via CI jobs or the "docker build, docker push, kubectl apply" cycle. It works, but this workflow is painful and incredibly slow.

Okteto - A Tool for Cloud Native Developers

Dev Lake brings all your DevOps data into one practical, personalized, extensible view. Ingest, analyze, and visualize data from an ever-growing list of developer tools, with our free and open source product. Dev Lake is most exciting for leaders and managers looking to make better sense of their development data, though it's useful for any developer looking to bring a more data-driven approach to their own practices. With Dev Lake you can ask your process any question, just connect and query.
 
Dev Lake provides understanding of software development lifecycle, digging workflow bottlenecks, Timely review of team performance, Rapid feedback, Agile adjustment. It helps to quickly build scenario-based data dashboards and drill down to analyze the root cause of problems.
 
<div>What can be accomplished with Dev Lake?</div><div> </div><ol><li>Collect DevOps performance data for the whole process</li><li>Share abstraction layer with similar tools to output standardized performance data</li><li>Built-in 20+ performance metrics and drill-down analysis capability</li><li>Support custom SQL analysis and drag and drop to build scenario-based data views</li><li>Flexible architecture and plug-in design to support fast access to new data sources</li></ol>

Dev Lake brings all your DevOps data into one practical, personalized, extensible view. Ingest, analyze, and visualize data from an ever-growing list of developer tools, with our free and open source product. Dev Lake is most exciting for leaders and managers looking to make better sense of their development data, though it's useful for any developer looking to bring a more data-driven approach to their own practices. With Dev Lake you can ask your process any question, just connect and query.

Dev Lake -  Data lake for Dev

Stern allows you to tail multiple pods on Kubernetes and multiple containers within the pod. Each result is color coded for quicker debugging. The query is a regular expression so the pod name can easily be filtered and you don't need to specify the exact id (for instance omitting the deployment id). If a pod is deleted it gets removed from tail and if a new pod is added it automatically gets tailed. 
 
When a pod contains multiple containers Stern can tail all of them too without having to do this manually for each one. Simply specify the container flag to limit what containers to show. By default all containers are listened to.

Stern allows you to tail multiple pods on Kubernetes and multiple containers within the pod. Each result is color coded for quicker debugging. The query is a regular expression so the pod name can easily be filtered and you don't need to specify the exact id (for instance omitting the deployment id). If a pod is deleted it gets removed from tail and if a new pod is added it automatically gets tailed. 

Stern - Multi pod and container log tailing for Kubernetes

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