Containerizing Databases at New Relic (What We Learned) Bryant - PowerPoint PPT Presentation

Containerizing Databases at New Relic (What We Learned) Bryant Vinisky and Joshua Galbraith Santa Clara, California | April 23th – 25th, 2018

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Introductions New Relic • A cloud platform to make every aspect of modern software and infrastructure observable! Bryant Vinisky • Senior Site Reliability Engineer • Database Engineering Team Joshua Galbraith • Senior Software Engineer • Database Engineering Team � 3

Agenda • Where We Started • Research • Prerequisites • Megabase • Monitoring • Lessons Learned • Outcomes � 4

Where We Started Databases at New Relic circa 2016

Database Management Issues 📧 Using Puppet for configuration and deployment 🚛 Slow delivery time due to timing of hardware orders 💹 Inefficient hardware use � 6

Why Containers? • Why not use virtual machines instead? • Why not use AWS? • Why not multi-tenant logical databases? � 7

Preparing for the Future 🤕 New Container Fabric for deploying our stateless apps 🚣 Future regions will be entirely container-based! 🛥 Incremental delivery of containerized databases? � 8

Setting Goals 📧 Packaging and Deployment • consistent and repeatable 🚛 Database Delivery Time • from months to minutes 💹 Cost Efficiency • reduce wasted resources � 9

Compressed Timeline 😆 Managing hundreds of existing, busy databases  Need to ship an MVP and gain traction quickly  Dev work is blocked on database delivery time � 10

Research A Survey of Open-Source Orchestration Tools

Open-Source Container Orchestration � 12

Stateful Containers: Mesos and Marathon Key Concepts • Dynamic Provisioning • Reservation Labels • Local Persistent Volumes • External Volumes � 13

Stateful Containers: Kubernetes Key Concepts • Stateful Sets • Pods • Headless Service • Persistent Volumes • Operators � 14

Stateful Containers: Nomad Key Concepts • Jobs • Task Groups • Allocations • Sticky Volumes • Volume Plugins • FS Drivers � 15

Joyent Blog: Autopilot for Databases � 16

Stateful Containers: Emergent Patterns Abstract Patterns • Application-aware orchestration • Autopilot pattern for lifecycle management • Storage fabrics and networked storage 😟 � 17

Stateful Containers: Current Status � 18

Making Trade-Offs • Dynamic Scheduling vs. Manual Placement • Custom Orchestration Framework vs. Client-Server • Distributed Consensus? • Local Object Storage? • Lifecycle Management logic inside or outside Container? � 19

Prerequisites Dynamic Inventory and/or Service Discovery

Problem: Database Inventory What systems do we have? What logical databases? What team is the owner? Naming standards? API and CLI access? � 21

Megabase Prerequisite: Inventory System Metadata on DB systems and services Percona containers on Megabase Golang service HTTP interface to DB Update on event and scheduled jobs Seed automation tasks � 22

Inventory System: Database • Query read only data from other systems and authorities • Megabase container deployment information • Provide basic service discovery � 23

Inventory System: HTTP Interface (JSON) Query over HTTP Return JSON � 24

Inventory System: HTTP Interface (text) � 25

Inventory System: Dynamic Lookups � 26

Megabase A platform for containerized databases at New Relic

Megabase: What We Built � 28

Megabase: Ingredients Bare Metal: • Kernel 4.4 and 4.14 • CentOS 7 and CoreOS Docker: 1.12 and 1.17 Image OS: • Alpine (Postgres and Redis) • Debian (Percona) Data stores: • Percona-server 5.6 • Percona-server 5.7 • Postgresql-server 9.3, 9.5 and 9.6 • Redis-server 3.2 Golang: 1.9 � 29

Megabase: Docker Image Building Dockerfile • Upstream base image • Custom labels • Package dependencies • Add binaries: - rclone - configuration sync - replication bootstrap • Entrypoint script � 30

Megabase: Docker Entrypoint Tasks • Validate data mount • Sync base configs from S3 • Apply dynamic configuration • No data => replication bootstrap/initdb • Start server processor � 31

Megabase: Injecting Configuration Strategies • Environment variables - via deploy config • Configuration files - via object storage - version controlled • Dynamic computation from cgroup limits • Docker images - via image registry � 32

Megabase API Server Pre/Post deployment dependencies Manage container runtime dependencies Interface to docker over https Support custom workflows for database services megabase server � 33

Megabase API: TLS Authentication Authenticate all requests with TLS client certificates � 34

Authentication Failure � 35

Authentication Success � 36

Megabase API: Endpoints � 37

Megabase API: Dependencies Containers expect and validate bind mount under data directory Megabase deploy pre-step to docker run: • Carve off extents for logical volume and make filesystem • Create systemd unit file for persistence and mount volume � 38

Megabase API: Create Logical Volume � 39

Megabase API: Container Runtime Reduce client config burden Offload predictable defaults: • Resource Limits • Bind mount volume to data directory • Host networking • Inject environment secrets Example docker run on cli => � 40

Megabase API: Failover Tasks � 41

Megabase API: Xtrabackup Stream to Peer � 42

Megabase… Client? “So we’re just supposed to type out those nasty, long curl commands to operate everything? Really? And TLS client auth too? Are you trying to be annoying?” - anonymous New Relic db-team member mb client � 43

Megabase Client: mb � 44

Megabase Client: mb mb: Command Line Interface • wrap up server API functionality into command line interface • transparently handle TLS authentication • query state, health and configuration across servers and deployments • coordinate deployments across servers • leverage inventory to resolve host and container names � 45

Megabase Client: mb � 46

Megabase Client: Deployment Manifest Minimum info required: • Container name • Image path and tag • CPU, memory and disk resources • VIP for load balancer and DNS • Owning team Auto select values if absent Define one or more containers � 47

Megabase Client: mb Deployment Process • Target environment and cluster • Specify a deployment manifest • Generate port and passwords • Send requests to API servers - new logical volume - run container • Check responses • Validate deployment - health � 48

Monitoring Using New Relic to Monitor New Relic