What are the most important considerations for implementing service mesh in your DevOps pipeline?

Before implementing a service mesh, its imperative to have a clear understanding of your microservices landscape - document the architecture, the technology stack in use, any dependencies, and your computational needs. Apart from the cost implications and technology stack compatibility, also consider the availability of community support, and the feature set (traffic management, security features, observability, customization, etc.) offered by the service. Ask questions like, will the service be able to handle future scalability requirements? Do you handle large amount of sensitive data? Consider implementing a small proof-of-concept and take it for a spin, before fully committing to a service mesh.

Choosing the right service mesh solution is the most important part of building your project. 1. Before you start evaluating the available options, consider understanding your requirements and your project network. 2. Your cloud platform will also play a significant role in your decision so that should be your second priority. 3. You should also consider budget and computational complexity for each available solution. If you’re looking for something that is easy to use and implement then go with a managed service however if you’re looking for a long term solution then evaluate everything before you decide to integrate it. It wont be easy to keep changing your solutions in the later stages so evaluating properly is essential.

In the world of micro-services and Kubernetes, Service mesh is critical for monitoring, traffic management and DR. Complexity: A service mesh can add complexity to your architecture. Ensure you genuinely need it and aren't just following the hype. Teams need to be trained to understand and troubleshoot the service mesh. Configuration Management: Service mesh solutions like Istio rely heavily on configuration. Implement configuration management and versioning to keep track of changes. Observability and Monitoring: Make sure you can monitor the service mesh itself and the services running within it. Utilize the service mesh's capabilities for distributed tracing, logging, and metrics collection.

1. How Big Your Sistem? 2. Using Monolith or Microservice? 3. How Many Programmer? 4. What Technology wanna used? ex. Language, Database server etc.

I think that starting with "choosing the right mesh" should not be the 1st topic. The 1st topic should be the explanation of what is the mesh in more details. For example: "Service Mesh typically can be thought of as a small proxy service that is connected to every service in your ecosystem. Every service talks to other services using those proxies. The first benefit it gives - is unified no-code logging and monitoring (proxies will log requests, not sender and receiver). Second benefit - access control, discoverability and configuration (proxies will handle "service directory" and "who can talk to whom"). Proxies can even block access or shape traffic dynamically, for example to prevent spreading of DDoS attacks."

This is where two key considerations need to be addressed: 1. You shouldn’t be having a service mesh architecture that only addresses to your existing network. The architecture should be responsible for maintaining future connections too and hence you shouldn’t develop anything that is tightly controlled by your existing infrastructure or application requirements. 2. Your service mesh components should be able to handle updates and configuration without having to worry about any issues that might arise from your deployments to the applications. This is critical part for the CICD pipeline. Once the controllers are deployed you have be able to manage them without having any effect on the uptime of your services.

Components of a Service Mesh: Data Plane: This typically consists of a set of lightweight network proxies deployed alongside your application code (often in the same Kubernetes pod). Proxy: These handle all network communication between your microservices. Examples include Envoy and Linkerd2-proxy. Control Plane: This provides an interface to control the behavior of the data plane. Management Server: This is where the configuration of proxies is managed. Istio's control plane, for instance, includes components like Pilot, Citadel, and Telemetry. Service Discovery: Helps proxies and services discover and communicate with each other.

Monitoring and troubleshooting a service mesh are critical to ensure optimal performance, security, and reliability of your microservices. Since a service mesh manages the communication between services, any issue can have cascading effects on your applications. Define your key metrics. Then Tools like Prometheus can scrape metrics from various service mesh components, especially if you're using a solution like Istio. Use Grafana for visualizing these metrics through dashboards. Distributed tracing tools like Jaeger or Zipkin can be integrated with most service meshes to track requests as they traverse multiple services. Ensure that logs from your applications, are aggregated using solutions like ELK Stack or Loki.

if you need inspiration, you can look at the opentelemetry project (a collection of APIs, SDKs, and tools) for models and standards

Monitoring and troubleshooting any devops component is difficult as there are many integration point. Incase of service mesh this becomes even more complicated as service mesh generates lot of logs and traces as compared to other components. Following is what you should consider: 1. Create meaningful dashboards that reflects the correct state of your underline infra. Lot of times issue with service mesh are related to the change in infra. 2. Logs are your friends. Don't loose them. 3. Isolate false positives by comparing previous states. 4. Define thresholds at every possible level and leverage the inbuild alerts of your tools. Most importantly do let your service mesh have a parallel monitoring & logging system of its own.

Securing a service mesh is essential as service meshes are becoming an integral part of microservices architectures. They offer capabilities like traffic management, observability, and security at the service-to-service communication level. Here are a couple of best practices: Mutual TLS (mTLS) Fine-grained RBAC (Role-Based Access Control) Policy Enforcement Network Policies Audit Logging Secure the Control Plane Regularly Update Your Service MeshObservability and Monitoring Secure the data plane Invest in API security

If not hardened properly, service mesh can become a single point of failure and a prefect gateway for mischief users. That's why its extremally important to treat service mesh as a peace of the over all project and build security controls around it like how you do for other project components. Following is what you should consider: 1. Dont have centralize mesh defined that can manage multiple environments. Its one service mesh per environment only. 2. Harden all access to it and never allow the public access to the service mesh endpoints. 3. Configure logging for all events 4. Never allow direct console changes via mesh UI

I architected a service mesh centered on Lua and OpenResty for authN and authZ. This choice optimized for adaptability and speed. But the true strength lay in implementing mutual TLS (mTLS). With mTLS, both the client and server undergo authentication, adding a robust layer of security. This approach encrypted and secured service-to-service traffic, negating unauthorized access risks. Harnessing these tools and protocols, we achieved a fortified communication pathway, enhancing overall system resilience.

If the benefits and requirement of using any tool are not clear then no matter how good the tool is, it wont last long in the project. Service mesh has a steep learning curve and its not straightforward to use and configure either. In order to manage mesh effectively and efficiently we need to keep the usecases simple in the bigging. There will be questions like, why do we need this if everything is working fine as is or why should I learn this tool if I'm not managing it and so on.. So make sure you identify with the common questions and plan out the training in such a way that everyone sees the business goal and potential long run benefit in what they are suppose to do.

Ensure your team understands the security best practices and potential threats related to service meshes. Regularly conduct security training and awareness sessions. Considering the dynamic nature of cloud-native technologies and the constant evolution of security threats, it's crucial to stay updated on best practices and industry standards. Additionally, participate in the community and learn from real-world incidents to adapt and strengthen your security posture.

A service mesh also consists of two parts ，which means the data panel and the control plane. As the names suggest, the data plane handles the actual forwarding of traffic, whereas the control plane provides the configuration and coordination.

Service Mesh’s implementation, adoption & operations is complex & has a steep learning curve. So, this should be seen as more of a Platform’s responsibility rather than that of Project/Product teams. When evaluating the capabilities of Service Mesh offerings, apart from the platform operator’s perspective one must also consider the developer experience (DevEx) of the target platforms & the crosscutting capabilities that can be provided to the application teams building for that platform. Predetermining & designing the platform for these capabilities help lower the cognitive load on the teams such that they focus more on their domain problems. The goal should be to offload the application teams to help simplify the application complexity.