From development to production

Transcription

1 David Barbarin From development to production

2 BIG Thanks to SQLSatMadrid sponsors Platinum Gold

3 > whoami David Barbarin Senior Consultant Architecture, Performance and high David Barbarin Blog

4 Agenda DevOps & containers Software lifecycle management Development and production scenario feedbacks Q/A

5 DevOps and containers

6 DevOps & containers DevOps Dev + Ops is the union of people, process and products to enable continuous delivery of value to end users > To provide quality of services to end users & To reduce the time-to-market > By changing the way to deal with changes (small batch size but more often to avoid spending too much time to the testing phase) > By giving (read) access to your developers on production to understand the impact of their work and to fix issues accordingly > It s not only about automation tool => Customers must be mature on their CI/CD processes to get real benefit of their automation pipeline > Breaking the boundaries between Dev and Ops (including DBAs) is important!!

7 DevOps & containers DevOps Containers can help > Traditional approch leads to developers and administrators to use different tools Traditional approch is difficult if infrastructure team is not enough agile to provide dev environments With Docker is both developers and ops use the same tool => Docker Docker images can be used locally and on DEV environment > Traditional dev environments are often being updated manually without automation Docker makes updates easy to automate and to deploy > Traditional dev environments can differ significantly from staging and production Immutable dev, staging and production environments leading to high level of control of changes Rollback to previous version is easy at any moment

8 Docker and software Lifecyle management

9 Docker and software Lifecycle management CI/CD pipeline Dependencies Performance.. Sanitized data Production QA / Preproduction Development Create test / dev environment Consume test / dev environment Automated deployment CD Other tests Create QA environment Push and check-in changes Scheduled tests CI

10 Development and Production scenario feedbacks

11 Development & Production scenario feedbacks DMK tool development runner Next step (currently in beta) => automated CI pipeline Gitlab > Versioning > Team collaboration Scheduled tests (beta version) -Identify regressions -Check performance impact SYNC??? Release 1 Release 1.2 Release 1.3 => 50 tests => 100 tests Code more complex Tests are time consumming - Push and Check-in - Unit tests Support of different versions of SQL Server since SQL Server 2008 (including Linux) New features added through SPs and CUs SQL Server 2008 SQL Server 2014 > Building and updating images are easy SQL Server 2016 > Lower resource footprint SQL Server 2017 > Images are easier to share between the team

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13 Development & Production scenario feedbacks Development Customer CI/CD & self-service environment > What about SQL Server versions prior to SQL2017? > I don t want to maintain myself Docker images > I want to provide a self-service environment for developers > What about disk space consumption? > What about Windows authentication?

14 Development & Production scenario feedbacks Development Customer CI/CD & self-service environment Backup DBs prod (copy_only) Generate cloned DBs image Spin up container CI Once per week Backup DBs prod (copy_only) Generate cloned DBs image Container ondemand Development unit tests Backup DBs prod (copy_only) Generate cloned DBs image Container Spin up container Bug fix

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16 Development & Production scenario feedbacks Production customer case Docker Engine standalone NFS Production leads to different concerns: > Product s maturity??? > Docker CE vs Docker EE (UCP, DTR, security, built-in monitoring..) > MSSQL Docker images are not production ready > Persistent storage?? (blocker for DB s adoption for a long time) > Configuration best practices / management / monitoring > Security (secrets/access isolation/networking/trusted images ) > Monitoring.. HA / Load balancing? > Orchestrators (Docker Swarm / Kubernetes / OpenShift ) > Cloud Provider solution (DbaaS) > New Docker deployment method => stacks / services

17 Development & Production scenario feedbacks Production customer case Production-ready database? Based image > FROM microsoft/mssql-server-linux:<tag> > mssql-cli, htop Installation > /opt/mssql/bin/ (binaries) Management tools? Configuration Best practices? > /var/opt/mssql/ (db files, tlog files, logs, secrets ) > disk = /u[0-9]* > tempdb configuration > Memory capping > Trace flags OS performance settings - Kernel settings - Disks settings - Swap files Maintenance > DMK maintenance Monitoring Performance Best practices? Index, stats, db check integrity Database backups? > SQL Server Built-in tools alerts, jobs > Third-party tool => InfluxDB, Grafana, Kankuru Security >Prevent using sa

18 Development & Production scenario feedbacks Production customer case HA Proxy Docker Engine Docker Engine Docker Engine NFS NFS

19 What s next? > We re getting customer requests about SQL Server on RedHat OpenShift > SQL Server 2019 with RedHat Certified images and AG support for K8s

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21 Any questions?

22 Thank you for attending!

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