Tyk VS prometheus

Tyk: An open-source API Gateway that is fast and scalable, running on either its own standalone server or alongside your existing nginx installation.

We're a friendly bunch at https://github.com/TykTechnologies/tyk - I'll gladly pick up onboarding contributors for some meaningful tasks, if you'd like to ease into it. Lots of tech debt to address, so it's more maintenance work, testing, introducing DDD, etc.

Traditional way to try an open-source project Tyk is an open source API gateway project. Organizations can control access to the gateway and protect the security of enterprises and organizations. To start with, I chose the traditional way, using docker-compose to install it, which requires the Git and Docker environment on the computer.

Amazon API Gateway AWS provides fully managed service for creating, publishing, maintaining, monitoring, and securing REST, HTTP, and WebSocket where developers can create APIs that access AWS or other web services, as well as data stored in the AWS Cloud. Kong API Gateway Kong Gateway is an open-source, lightweight API gateway optimized for microservices, delivering unparalleled latency performance and scalability. If you just want the basics, this option will work for you. It is scalable easily horizontally by adding more nodes. It supports large and variable workloads with very low latency. Other API Gateways Apigee API Gateway MuleSoft Tyk.io Akana SwaggerHub Azure API Gateway Express API Gateway Karken D Choosing the right API gateway Some of the common baseline for evaluation criteria include simplicity, open-source vs propriety, scalability & flexibility, security, features, community, administrative (support, monitoring & deployment), environment provisioning(installation, configuration, hosting offering), pricing, and documentation. API Composition / Aggregation Some API requests in API Gateway map directly to single service API which can be served by routing request to the corresponding microservice. However, in the case of complex API operations that requires results from several microservices can be served by API composition/aggregation (a scatter-gather mechanism). In case of dependency of one another service where synchronous communication is required, the chained composition pattern has to be followed. The composition layer has to support a significant portion of ESB/integration capabilities such as transformations, orchestration, resiliency, and stability patterns. A root container is deployed with the special distributor and aggregator functionalities (or microservices). The distributor is responsible for breaking down into granular tasks and distributing those tasks to microservice instances. The aggregator is responsible for aggregating the results derived by business workflow from composed microservice. API Gateway and Aggregation API gateway with added features results in overambitious gateways that encourage designs that continue to be difficult to test and deploy. It is highly recommended to avoid aggregation and data transformation in the API Gateway. Domain smarts are better suited to be done in application code that follows the defined software development practices. Netflix API Gateway, Zuul 2 removed a lot of the business logic from Gateway that they had in Zuul to origin systems. For more details, refer here. Service Mesh and API Gateway Service mesh in microservices is a configurable network infrastructure layer that handles interprocess communication. This is akin to what is often termed as sidecar proxy or sidecar gateway. It provides a lot of functionalities such as:

It's like Prometheus, but for logs. Okay it's not really to do with the Norse or Greek gods, instead Loki is a horizontally-scalable, highly-available, multi-tenant log aggregation system inspired by the open source project Prometheus. Built by Grafana Labs, Loki is designed for ease of use. Instead of indexing the contents of the logs, Loki provides a set of labels for each log stream. The latest update includes query acceleration with Bloom filters, native OTel support, Helm charts, and more. Check out the changelog for all the major changes and deprecations.

WriteRequest::timeseries is a vector (https://github.com/prometheus/prometheus/blob/main/prompb/re...) and

Developers widely use Prometheus as a system for operational monitoring and alerting for their projects. Here is a list of tools for monitoring frontend services with Prometheus.

Just to give an example of the power of Go for CLI builds, you may have already used or at least heard of Docker, Kubernetes, Prometheus, Terraform, but what do they all have in common? They all have a large part of their usability via CLI and are developed in Go 🐿.

Distributed system administrators need mechanisms and tools for monitoring individual nodes in order to analyze the system and promptly detect anomalies. Developers also need effective mechanisms for analyzing, diagnosing issues, and identifying bugs in protocol implementations. Logging, tracing, and collecting metrics are common observability techniques to allow monitoring and obtaining diagnostic information from the system; most of the explored code bases use these techniques. OpenTelemetry and Prometheus are popular open-source monitoring solutions, which are used in many of the explored code bases.

Setting up monitoring for a system, especially one involving GRPC communication, provides crucial visibility into its operations. In this guide, we walked through the steps to instrument both a GRPC server and client with Prometheus metrics, exposed those metrics via an HTTP endpoint, and visualized them using Grafana. The Docker-Compose setup simplified the deployment of both Prometheus and Grafana, ensuring a streamlined process.

Alerting and Notification: Select a tool with flexible alerting mechanisms to proactively detect anomalies or deviations from defined thresholds. Consider asking questions like "Does this tool offer customizable alerting options and support notification channels that suit our team's communication preferences?" A tool like Prometheus provides robust alerting capabilities.

Prometheus

Prometheus is an open-source monitoring and alerting toolkit. It is designed to monitor highly dynamic containerized systems, making it an excellent choice for monitoring Docker containers and Kubernetes clusters.