Elastic{ON} Tour Seattle - Elastic Cloud Enterprise

Elastic{ON} Tour Seattle - October 5, 2017

Learn how Elastic Cloud Enterprise can help your Elastic Stack projects.

Catherine Johnson | Director, AMER West Sales Engineering | Elastic

Transcript

1. 1 Catherine Johnson Director, AMER West Sales Engineering Elastic Cloud Enterprise
2. 2 The Customer Journey Initial download & prototype LAB & Staging Production Expansion Process Repeats Elastic Adoption process Production Build-out
3. 3 The Typical Elastic Adoption Pattern More data More use cases More tenants
4. 4 What’s Wrong with One Big Cluster? Tenants • Different data lifecycles • Different access profiles • Expect different SLAs • Different backup policies • Different versions Operations • Maintenance windows are difficult • Fair use is hard, to impossible • Upgrades affect all tenants • Data isolation is not complete • KibanaS VS
5. 5 The Elastic Stack moves quickly 5 New minor version every 30-60 days Major version release every 12 months Version Release Date 2.0 Oct 28 2015 5.0 Oct 26 2016 6.0 Fall 2017 (planned) Patch version can come every couple of weeks or faster 5.3 Mar 28 2017 5.4 May 04 2017 5.5 July 06 2017 5.6 Sep 11 2017 5.5.1 Jul 25 2017 5.5.2 Aug 17 27 2017 5.5.3 Sep 11 2017
6. 6 Time to Split!
7. 7 Time to Split!
8. 8 Splitting Is Not Easy… • How do you split? (by volume, tenant, use case, access profile) ‒ When one tenant gets its own cluster, the others will want one too • You now have multiple clusters to manage ‒ Different Elasticsearch versions ‒ Different support SLAs ‒ Different HW? Same HW? How do you isolate resources? ‒ What about backups? ‒ What about security? ‒ How do you even track and monitor all of this? Architectural decisions informed by business need
9. 9 We Actually Do All Of This And we do it today, on our SaaS offering Elastic Cloud
10. 10 Provisioning, orchestration, and management of multiple clusters Deployed on-premise, in your private cloud … or wherever you want Leverages the same technology used in Elastic Cloud Automates frequent tasks such as snapshot/restore, upgrade and scale
11. • Streamline “janitorial” tasks – Snapshotting (backups) – Upgrading - easier to manage velocity of releases – Creating, deleting, scaling – API • Resource usage visibility and optimization – Single pane of glass for tracking all clusters in your environment – Optimized resource utilization and isolation through containerization and centralized resource allocation • Built in best practices – All clusters are secure by default – Optimal settings and architecture for each cluster – Leverage production features for more proactive, less reactive work Major Benefits
12. Our experience wrapped into a product
15. 15 15 WHAT CAN YOU USE IT FOR?
16. 16 Multiple Applications, Multiple Clusters
17. 17 Centralized Logging LOG ANALYTICS LOG ANALYTICS LOG ANALYTICS LOG ANALYTICS LOG ANALYTICS LOG ANALYTICS LOG ANALYTICS LOG ANALYTICS LOG ANALYTICS LOG ANALYTICS
18. 18 Multiple Environments Dev, Test, QA, Prod
19. 19 What Use Cases Should You Be Looking For? • As a backing service for PaaS / SaaS ‒ Service Brokers for CloudFoundry and OpenShift ‒ Cluster per customer in a SaaS app • Easily create a cluster per user / tenant • Maintain isolation between users and tenants Discovering new uses inside of your business
20. 20 20 DEMO
21. 21 21 ARCHITECTURE
22. 22 High Level Architecture Allocator Cloud UI Admin API ZooKeeper + Director Constructor Allocator ES Admin Cluster Allocator ES Logging Cluster Allocator Load Balancer (User supplied) Proxy Proxy Proxy + HTTP + HTTPS TLS Over Stunnel HTTPS Admin User HTTPS Allocator HTTPS HTTPS Runner Client Forwarder Beats
23. 23 Thank you!