Rusty  Shanahan

Rusty Shanahan

1593318060

How to Achieve Engineering Efficiency with a Service Mesh

As the idea for Aspen Mesh was formulating in my mind, I had the opportunity to meet with a cable provider’s engineering and operations teams to discuss the challenges they had operating their microservice architecture. When we all gathered in the large, very corporate conference room and exchanged the normal introductions, I could see that something just wasn’t right with the folks in the room. They looked like they had been hit by a truck. The reason for that is what turned this meeting into one of the most influential meetings of my life.

It turned out that the entire team had been up all night working on an outage in some of the services that were part of their guide application. We talked about the issue, how it manifested itself and what impact it had on their customers. But there was one statement that has stuck with me since: “The worst part of this 13-hour outage was that it took us 12 hours to get the right person on the phone; and only one hour to get it fixed…”

That is when I knew that a service mesh could solve this problem and increase the engineering efficiency for teams of all sizes. First, by ensuring that in day-to-day engineering and operations, experts were focused on what they were experts of. And second, when things went sideways, it was the strategic point in the stack that would have all the information needed to root-cause a problem — but also be the place that you could rapidly restore your system.

Day-to-Day Engineering and Operations

A service mesh can play a critical role in day-to-day engineering and operations activities, by streamlining processes, reducing test environments and allowing experts to perform their duties independent of application code cycles. This allows DevOps teams to work more efficiently, by allowing developers to focus on providing value to the company’s customers through applications and operators to provide value to their customers through improved customer experience, stability and security.

The properties of a service mesh can enable your organization to run more efficiently and reduce operating costs. Here are some ways a service mesh allows you to do this:

  • Canary testing of applications in production can eliminate expensive staging environments
  • Autoscaling of applications can ensure efficient use of resources.
  • Traffic management can eliminate duplicated coding efforts to implement retry-logic, load-balancing and service discovery.
  • Encryption and certificate management can be centralized to reduce overhead and the need to make application changes and redeployment for changing security policies.
  • Metrics and tracing gives teams access to the information they need for performance and capacity planning, and can help reduce rework and over-provisioning of resources.

As organizations continue to shift-left and embrace DevOps principles, it is important to have the right tools to enable teams to move as quickly and efficiently as possible. A service mesh helps teams achieve this by moving infrastructure-like features out of the individual services and into the platform. This allows teams to leverage them in a consistent and compliant manner; it allows Devs to be Devs and Ops to be Ops, so together they can truly realize the velocity of DevOps.

#devops #service mesh #contributed #sponsored

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How to Achieve Engineering Efficiency with a Service Mesh

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Roberta  Ward

Roberta Ward

1598169240

From Service Mess to Service Mesh

Introduction

Over the last 10 years, the rapid adoption of microservices architecture has resulted in enterprises with hundreds or (sometimes even thousands) of services. With the growth of containerization technologies like Docker and Kubernetes, microservice patterns have seen the strongest growth; resulting in a complex dependency matrix between these micro-services. For teams to monitor, support, and to maintain these services is becoming a challenge so most enterprises have invested in some kind of microservices management tool.

This article will explore some of the common aspects of microservice management. Then we’ll take a closer look at the centralized gateway pattern, as well as its limitations (most enterprises have started with or currently still use this pattern). Then we will look into a new pattern called “Service Mesh” which has gained a lot of attention in the last 3–4 years. Often this pattern is also referred to as the “Side Car Proxy”. So lets get started!

Micro-Services Management

As enterprises start building more and more microservices, it’s becoming clear that some of the aspects of microservices are common across all microservices. So it makes sense to provide a common platform for managing these common aspects. Below are some of the key common aspects:

Service Registration and Discovery: A commonplace to register, document, search and discover microservices

Service Version Management: Ability to run multiple versions of a microservice.

**Authentication and Authorization: **Handle authentication and authorization including Mutual TLS (MTLS) between services.

Service Observability: Ability to monitor end to end traffic between services, response times, and quickly identify failures and bottlenecks.

**Rate Limiting: **Define threshold limits that traffic services can handle.

Circuit Breaker: Ability to configure and introduce a circuit breaker in case of failure scenarios (to avoid flooding downstream services with requests).

**Retry Logic: **Ability to configure and introduce retry logic dynamically in services.

So it’s a good idea to build these concerns as part of a common framework or service management tool. As a result, micro-service development teams don’t have to build these aspects in the service itself.

#service-mesh #istio-service-mesh #microservices #gateway-service #envoy-proxy

Fannie  Zemlak

Fannie Zemlak

1597494060

Open Service Mesh — Microsoft’s SMI based Open Source Service Mesh Implementation

Microsoft’s Open Service Mesh is an SMI-compliant, lightweight service mesh being run as an open source project. Backed by service-mesh partners including HashiCorp, Solo.io, and Buoyant, Microsoft introduced the Service Mesh Interface last year with the goal of helping end users and software vendors work with the myriad choices presented by service mesh technology by providing a set of specification standards. OSM can be considered as a reference implementation of SMI, one that builds on existing service mesh components and concepts.

Open Service Mesh data plane is architecturally based on the Envoy proxy and implements the go-control-plane xDS v3 API. However, despite the fact that Envoy comes with OSM by default, using standard interfaces allows it to be integrated with other reverse proxies (compatible with xDS).

SMI follows in the footsteps of existing Kubernetes resources, like Ingress and Network Policy, which also do not provide an implementation where required interfaces to interact with Kubernetes are facilitated for providers to plug their products. The SMI specification instead defines a set of common APIs that allow mesh providers to deliver their own implementations. This means mesh providers can either use SMI APIs directly or build operators to translate SMI to native APIs.

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SMI Implementation

With OSM, users can use SMI and Envoy on Kubernetes and get a simplified service-mesh implementation. The SMI ecosystem already has multiple providers like Istio, Linkerd, Consul Connect, now Open Service Mesh etc. some of them have implemented SMI compatibility using adaptors (Istio, Consul Connect) and others (OSM, Linkerd etc.) consume the SMI APIs directly.

OSM implementation is very similar to Linkerd which also directly consumes SMI APIs without any need for an adaptor like Istio, but one key difference is that OSM uses Envoy for its proxy and communication bus, whereas Linkerd uses linkerd2-proxy (rust based — lighter than Envoy).

Architecture & Components

OSM control plane comprise four core components. All these four components are implemented as a single controller entity (Kubernetes pod/deployment), this is much lighter in weight when compared with older versions of Istio where there are 4 control plane components (Istio-1.6 introduced istiod which unifies all the control plane components into one binary).

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OSM Architecture — Components

OSM Data Plane — Uses Envoy as reverse-proxy by default — similar to most other Service Mesh providers (Linkerd is unique in this case which uses ultralight transparent proxy written in Rust). While by default OSM ships with Envoy, the design utilizes interfaces (An interface type in Go is kind of definition. It defines and describes the exact methods that some other type must have), which enable integrations with any xDS compatible reverse-proxy. The dynamic configuration of all the proxies is handled by OSM controller using Envoy xDS go-control-plane.

#service-mesh #istio-service-mesh #kubernetes #azure #microsoft

Rusty  Shanahan

Rusty Shanahan

1593318060

How to Achieve Engineering Efficiency with a Service Mesh

As the idea for Aspen Mesh was formulating in my mind, I had the opportunity to meet with a cable provider’s engineering and operations teams to discuss the challenges they had operating their microservice architecture. When we all gathered in the large, very corporate conference room and exchanged the normal introductions, I could see that something just wasn’t right with the folks in the room. They looked like they had been hit by a truck. The reason for that is what turned this meeting into one of the most influential meetings of my life.

It turned out that the entire team had been up all night working on an outage in some of the services that were part of their guide application. We talked about the issue, how it manifested itself and what impact it had on their customers. But there was one statement that has stuck with me since: “The worst part of this 13-hour outage was that it took us 12 hours to get the right person on the phone; and only one hour to get it fixed…”

That is when I knew that a service mesh could solve this problem and increase the engineering efficiency for teams of all sizes. First, by ensuring that in day-to-day engineering and operations, experts were focused on what they were experts of. And second, when things went sideways, it was the strategic point in the stack that would have all the information needed to root-cause a problem — but also be the place that you could rapidly restore your system.

Day-to-Day Engineering and Operations

A service mesh can play a critical role in day-to-day engineering and operations activities, by streamlining processes, reducing test environments and allowing experts to perform their duties independent of application code cycles. This allows DevOps teams to work more efficiently, by allowing developers to focus on providing value to the company’s customers through applications and operators to provide value to their customers through improved customer experience, stability and security.

The properties of a service mesh can enable your organization to run more efficiently and reduce operating costs. Here are some ways a service mesh allows you to do this:

  • Canary testing of applications in production can eliminate expensive staging environments
  • Autoscaling of applications can ensure efficient use of resources.
  • Traffic management can eliminate duplicated coding efforts to implement retry-logic, load-balancing and service discovery.
  • Encryption and certificate management can be centralized to reduce overhead and the need to make application changes and redeployment for changing security policies.
  • Metrics and tracing gives teams access to the information they need for performance and capacity planning, and can help reduce rework and over-provisioning of resources.

As organizations continue to shift-left and embrace DevOps principles, it is important to have the right tools to enable teams to move as quickly and efficiently as possible. A service mesh helps teams achieve this by moving infrastructure-like features out of the individual services and into the platform. This allows teams to leverage them in a consistent and compliant manner; it allows Devs to be Devs and Ops to be Ops, so together they can truly realize the velocity of DevOps.

#devops #service mesh #contributed #sponsored

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