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Kubernetes meetup: Networking for Microservices


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These slides describe how Contiv networking works with Kubernetes

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Kubernetes meetup: Networking for Microservices

  1. 1. Kubernetes Meetup #8 Networking for Microservcies Sukhesh Halemane @shaleman Joji Mekkat @jojimt April 21
  2. 2. • Container Networking and Storage with Ops Policies • Provides Northbound Integration: entire policy model exposed natively – Besides REST interfaces, auto-generated Go/Python clients • Open Sourced at Contiv - Introduction  Container Connectivity  Policies for networking  Variety of connectivity options  Works with Kubernetes, Docker, Mesos, Nomad Contiv Networking  Policy for volume allocation  Snapshots, IOPs rate-limiting, Garbage Collection, etc.  Works with Docker Contiv Storage  Node Discovery, Inventory  Node Life-Cycle Management  Complete Stack, managed  Works for cloud, optimized for Bare-Metal Contiv Cluster Contiv UI
  3. 3. • Kubernetes Networking Plugin • Kubernetes provides a very flexible and open plugin interface • Enables wider datacenter use cases Contiv Networking Microservice Aware • Segmentation and policies per Microservice • Service discovery and routing • Application telemetry and visibility Physical Network Integration • Pure L3 Routed Networks • Classic L2 and overlay networks • Cisco SDN solutions • Features • Fully multi tenant • Built in IPAM • Public/private cloud deployments Single Forwarding pipeline • High performance Openflow based pipeline in kernel • Highly programmable and extensible • IP Routing, security policies, L4 load balancing and telemetry in single switching pipeline
  4. 4. Contiv Networking Architecture Contiv Master Contiv Master Contiv Master Contiv Master Contiv Master Collector Host 1 Contiv Datapath Contiv Agent Host 2 Contiv Agent Host 3 Contiv Datapath Contiv Datapath Contiv UI Contiv Agent
  5. 5. Microservices == Distributed Systems • Problems of distributed systems – Complex calling patterns – RPC mechanisms • How can networking help? • Connectivity maps: who is talking to who • Historical Data for Application Tuning/Characterization • No need for code instrumentation or running agents • Always-on logging can serve as audit trail • E.g. who accessed DB tier and if they were authorized accesses
  6. 6. Application Telemetry • What data to collect? • Time-stamped Interactions between containers and services • Flow level stats (5 or 7 tuple) • Per container Stats • Rx/Tx Bytes and Packets • TCP connection lengths (Syn/Fin correlation) • Security Policy violations • Bandwidth consumption • Challenges • Granularity • Between micro-services, Between containers, Flows (protocol/port), REST calls • Frequency and sampling • How to handle transient flows? • Scale • Analytics • Providing a Nicer way to consume it
  7. 7. DEMO
  8. 8. Kuber: On demand taxi app APP DB APP Passenger DBAPPPassenger APP APP DB APP Driver DB APP Driver APP APP DB APP Trips DB APP Trips APP APP DB APP Payments DBAPPPayments APP Web Web Web Web Web Web Web Web
  9. 9. Thank you Find us on Github