What is linkerd and what are its top alternatives?
Top Alternatives to linkerd
Istio is an open platform for providing a uniform way to integrate microservices, manage traffic flow across microservices, enforce policies and aggregate telemetry data. Istio's control plane provides an abstraction layer over the underlying cluster management platform, such as Kubernetes, Mesos, etc. ...
HAProxy (High Availability Proxy) is a free, very fast and reliable solution offering high availability, load balancing, and proxying for TCP and HTTP-based applications. ...
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. ...
Hystrix is a latency and fault tolerance library designed to isolate points of access to remote systems, services and 3rd party libraries, stop cascading failure and enable resilience in complex distributed systems where failure is inevitable. ...
Consul is a tool for service discovery and configuration. Consul is distributed, highly available, and extremely scalable. ...
Originally built at Lyft, Envoy is a high performance C++ distributed proxy designed for single services and applications, as well as a communication bus and “universal data plane” designed for large microservice “service mesh” architectures. ...
Conduit is a lightweight open source service mesh designed for performance, power, and ease of use when running applications on Kubernetes. Conduit is incredibly fast, lightweight, fundamentally secure, and easy to get started with. ...
nginx [engine x] is an HTTP and reverse proxy server, as well as a mail proxy server, written by Igor Sysoev. According to Netcraft nginx served or proxied 30.46% of the top million busiest sites in Jan 2018. ...
linkerd alternatives & related posts
- Zero code for logging and monitoring13
- Service Mesh8
- Great flexibility7
- Ingress controller4
- Easy integration with Kubernetes and Docker3
- Full Security3
- Powerful authorization mechanisms3
- Load balancer130
- High performance100
- Very fast69
- Proxying for tcp and http58
- SSL termination55
- Open source31
- Very popular12
- Runs health checks on backends7
- Suited for very high traffic web sites7
- Ready to Docker5
- Powers many world's most visited sites4
- Work with NTLM2
- Ssl offloading2
- Becomes your single point of failure4
related HAProxy posts
Around the time of their Series A, Pinterest’s stack included Python and Django, with Tornado and Node.js as web servers. Memcached / Membase and Redis handled caching, with RabbitMQ handling queueing. Nginx, HAproxy and Varnish managed static-delivery and load-balancing, with persistent data storage handled by MySQL.
We're using Git through GitHub for public repositories and GitLab for our private repositories due to its easy to use features. Docker and Kubernetes are a must have for our highly scalable infrastructure complimented by HAProxy with Varnish in front of it. We are using a lot of npm and Visual Studio Code in our development sessions.
- Leading docker container management solution161
- Simple and powerful126
- Open source102
- Backed by google75
- The right abstractions56
- Scale services24
- Replication controller19
- Permission managment9
- Supports autoscaling7
- No cloud platform lock-in4
- Open, powerful, stable3
- Quick cloud setup3
- Promotes modern/good infrascture practice3
- Backed by Red Hat2
- Cloud Agnostic2
- Runs on azure2
- Custom and extensibility2
- Captain of Container Ship2
- A self healing environment with rich metadata2
- Easy setup1
- Everything of CaaS1
- Poor workflow for development14
- Steep learning curve12
- Orchestrates only infrastructure6
- High resource requirements for on-prem clusters3
related Kubernetes posts
How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:
Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.
Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:
Visual Studio Code worked really well for us as well, it worked well with all our polyglot services and the .Net core integration had great cross-platform developer experience (to be fair, F# was a bit trickier) - actually, each of our team members used a different OS (Ubuntu, macos, windows). Our production deployment ran for a time on Docker Swarm until we've decided to adopt Kubernetes with almost seamless migration process.
After our positive experience of running .Net core workloads in containers and developing Tweek's .Net services on non-windows machines, C# had gained back some of its popularity (originally lost to Node.js), and other teams have been using it for developing microservices, k8s sidecars (like https://github.com/Soluto/airbag), cli tools, serverless functions and other projects...
- Cirkit breaker2
related Hystrix posts
- Great service discovery infrastructure58
- Health checking35
- Distributed key-value store27
- Token-based acls10
- Gossip clustering6
- Dns server5
- Not Java2
- Docker integration1
related Consul posts
As we've evolved or added additional infrastructure to our stack, we've biased towards managed services. Most new backing stores are Amazon RDS instances now. We do use self-managed PostgreSQL with TimescaleDB for time-series data—this is made HA with the use of Patroni and Consul.
We also use managed Amazon ElastiCache instances instead of spinning up Amazon EC2 instances to run Redis workloads, as well as shifting to Amazon Kinesis instead of Kafka.
Since the beginning, Cal Henderson has been the CTO of Slack. Earlier this year, he commented on a Quora question summarizing their current stack.Apps
- Desktop: And Electron to ship it as a desktop application.
- Android: a mix of Java and Kotlin.
- iOS: written in a mix of Objective C and Swift.
- The core application and the API written in PHP/Hack that runs on HHVM.
- The data is stored in MySQL using Vitess.
- Caching is done using Memcached and MCRouter.
- The search service takes help from SolrCloud, with various Java services.
- The messaging system uses WebSockets with many services in Java and Go.
- Load balancing is done using HAproxy with Consul for configuration.
- Most services talk to each other over gRPC,
- Some Thrift and JSON-over-HTTP
- Voice and video calling service was built in Elixir.
- Built using open source tools including Presto, Spark, Airflow, Hadoop and Kafka.
related Envoy posts
At uSwitch we wanted a way to load balance between our multiple Kubernetes clusters in AWS to give us added redundancy. We already had ingresses defined for all our applications so we wanted to build on top of that, instead of creating a new system that would require our various teams to change code/config etc.
Envoy seemed to tick a lot of boxes:
- Loadbalancing capabilities right out of the box: health checks, circuit breaking, retries etc.
- Tracing and prometheus metrics support
- Good community support
This was all good but what really sold us was the api that supported dynamic configuration. This would allow us to dynamically configure envoy to route to ingresses and clusters as they were created or destroyed.
To do this we built a tool called Yggdrasil using their Go sdk. Yggdrasil effectively just creates envoy configuration from Kubernetes ingress objects, so you point Yggdrasil at your kube clusters, it generates config from the ingresses and then envoy can loadbalance between your clusters for you. This is all done dynamically so as soon as new ingress is created the envoy nodes get updated with the new config. Importantly this all worked with what we already had, no need to create new config for every application, we just put this on top of it.
We are looking to configure a load balancer with some admin UI. We are currently struggling to decide between NGINX, Traefik, HAProxy, and Envoy. We will use a load balancer in a containerized environment and the load balancer should flexible and easy to reload without changes in case containers are scaled up.
related Conduit posts
- High-performance http server1.4K
- Easy to configure727
- Open source606
- Load balancer529
- Web server223
- Easy setup135
- Content caching29
- Web Accelerator20
- Reverse Proxy7
- Supports http/26
- The best of them5
- Enterprise version4
- Lots of Modules4
- Great Community4
- Reversy Proxy3
- High perfomance proxy server3
- Streaming media3
- Embedded Lua scripting3
- Streaming media delivery3
- Fast and easy to set up2
- Narrow focus. Easy to configure. Fast1
- Ingress controller1
- Virtual hosting1
- Along with Redis Cache its the Most superior1
- Advanced features require subscription8
related NGINX posts
Recently I have been working on an open source stack to help people consolidate their personal health data in a single database so that AI and analytics apps can be run against it to find personalized treatments. We chose to go with a #containerized approach leveraging Docker #containers with a local development environment setup with Docker Compose and nginx for container routing. For the production environment we chose to pull code from GitHub and build/push images using Jenkins and using Kubernetes to deploy to Amazon EC2.
We also implemented a dashboard app to handle user authentication/authorization, as well as a custom SSO server that runs on Heroku which allows experts to easily visit more than one instance without having to login repeatedly. The #Backend was implemented using my favorite #Stack which consists of FeathersJS on top of Node.js and ExpressJS with PostgreSQL as the main database. The #Frontend was implemented using React, Redux.js, Semantic UI React and the FeathersJS client. Though testing was light on this project, we chose to use AVA as well as ESLint to keep the codebase clean and consistent.
We switched to Traefik so we can use the REST API to dynamically configure subdomains and have the ability to redirect between multiple servers.
We still use nginx with a docker-compose to expose the traffic from our APIs and TCP microservices, but for managing routing to the internet Traefik does a much better job
The biggest win for naologic was the ability to set dynamic configurations without having to restart the server