Cloudlets and DevOps - A Dangerously Powerful Combination to Extend Capabilities to the Edge

1. © AKAMAI - EDGE 2017 Cloudlets and DevOps – A dangerously powerful combination to add agility into your app suite Les Waltman lwaltman@akamai.com

2. © AKAMAI - EDGE 2017 Customer Feedback I want to offload more to the Edge

3. © AKAMAI - EDGE 2017 Customer Feedback If only Akamai could let me do…

4. © AKAMAI - EDGE 2017 Customer Feedback Make it SIMPLE

5. © AKAMAI - EDGE 2017 Grow revenue opportunities with fast, personalized web experiences and manage complexity from peak demand, mobile devices and data collection. …and offload logic to the Edge What if you could take work…

6. © AKAMAI - EDGE 2017 WHAT ARE CLOUDLETS?  Micro Services executed at the Edge  Outsources:  Application code and lifecycle  Computing Capacity

7. © AKAMAI - EDGE 2017 WHY CLOUDLETS FOR DEVOPS?  Offload work that would otherwise be done at Origin  Logic is completed at the Edge  Self-servicable  Granular user access permissions  Configure through Luna UI, API, Akamai CLI, or CSV import

8. © AKAMAI - EDGE 2017 Grow revenue opportunities with fast, personalized web experiences and manage complexity from peak demand, mobile devices and data collection. Use CaseRedirect logic at the edge

9. © AKAMAI - EDGE 2017 Real life example Geo specific redirects, logic at Origin lead to significant latency

10. © AKAMAI - EDGE 2017 Edge Redirector Use Cases • Offload large redirect databases • Use cookie to apply business logic to redirects • Direct users based on their characteristics • Granular permissions allow business users to only access specific policies • Possibilities are only limited to what we know about the user

11. © AKAMAI - EDGE 2017 How DevOps work with Cloudlets API Luna Portal CSV File (uploaded via API or Luna) Akamai CLI

12. © AKAMAI - EDGE 2017 Grow revenue opportunities with fast, personalized web experiences and manage complexity from peak demand, mobile devices and data collection. Use CaseManage traffic surges

13. © AKAMAI - EDGE 2017 Prioritized User* Visitor How Visitor Prioritization Works Normal Traffic Flow ● All users are routed to the application in normal traffic flow ● Application can become overloaded During Application Overload ● Prioritized users are directed to the application ● During a traffic surge site administrators can adjust the rate normal users will be let into to a waiting room or directed to the application Waiting Room Back-end Application In high demand Back-end Application Prioritized User* Visitor Akamai Edge Server Akamai Edge Server Fig. 1: Normal Traffic Fig. 2: Application Overload * During traffic surges prioritized users take precedence over normal users Akamai Edge Server Akamai Edge Server each cycle, probability settings determine when users will be routed to the application

14. © AKAMAI - EDGE 2017 Waiting Room Example The Ticket Market The Ticket Market Just a moment ... You are in a waiting room due to high demand and we are working hard to fulfill every request. We want you to get your tickets as soon as possible. Please do not go anywhere, do not log off or refresh your page. At The Ticket Market our fans come first and we thank you for your patience. Terms and Conditions | Privacy Policy | Help Your one-stop shop for the best in live entertainment Branded waiting room experiences: games, discount coupons, countdown ticker, videos, ads Not having a waiting room leads to a poor user experience: error pages, blank or timed out screens.

15. © AKAMAI - EDGE 2017 Create Controlled, Scalable Experiences Selectively funnel users to the application based on predefined traffic segments matching: • Host • Cookie • Device Characteristics • File Extension • Query String • Geography (continent/country/region) Waiting Room Waiting Room Waiting Room 3 2 1 10% 50% 80%

16. © AKAMAI - EDGE 2017 Grow revenue opportunities with fast, personalized web experiences and manage complexity from peak demand, mobile devices and data collection. The Cloudlet Approach to 1. Initialize and configure base service using Luna 2. Operate (activate, throttle, etc.) via integration methods (API or Akamai CLI)

17. © AKAMAI - EDGE 2017 Use Cases Commerce/ Travel Media & Entertainment Public Sector Financial Services Retailers running a flash sale can track cookies to send visitors with a large amount in their shopping cart directly to check out. Broadcasters with Live Events can use the application to ensure viewers can login/register for their event and gain access to the page where the live video event is being hosted. Banks can use this application during the rush they experience during tax season to ensure customers can access banking applications and there is not a negative brand perception caused by a poor performing or inaccessible application. Charities that are looking to accept donations on a large scale during a disaster relief event. Universities that have large volumes of registrations or class schedule selections happening at the same time.

18. © AKAMAI - EDGE 2017 Grow revenue opportunities with fast, personalized web experiences and manage complexity from peak demand, mobile devices and data collection. Use CaseReleasing new, frequent software releases

19. © AKAMAI - EDGE 2017 originB.website.com originA.website.com 100% ● Gradually shift all or a segment of your visitors to test a new experience without impacting your entire visitor base ● Failback immediately should you encounter a problem ● Control cookies to maintain stickiness - even during failover All visitors are being directed to Origin A How Phased Release Works

20. © AKAMAI - EDGE 2017 originB.website.com originA.website.com 100% 100% ● Gradually shift all or a segment of your visitors to test a new experience without impacting your entire visitor base ● Failback immediately should you encounter a problem ● Control cookies to maintain stickiness - even during failover All visitors are being directed to Origin A How Phased Release Works

21. © AKAMAI - EDGE 2017 originB.website.com originA.website.com 100% Edge server assigns session cookie Cookie used to maintain stickiness 95% 5% ● Gradually shift all or a segment of your visitors to test a new experience without impacting your entire visitor base ● Failback immediately should you encounter a problem ● Control cookies to maintain stickiness - even during failover 15% of “orange” visitors are being directed to Origin B How Phased Release Works

22. © AKAMAI - EDGE 2017 originB.website.com originA.website.com 100% 100% ● Gradually shift all or a segment of your visitors to test a new experience without impacting your entire visitor base ● Failback immediately should you encounter a problem ● Control cookies to maintain stickiness - even during failover All visitors are being directed to Origin A How Phased Release Works

23. © AKAMAI - EDGE 2017 originB.website.com originA.website.com 100% ● Gradually shift all or a segment of your visitors to test a new experience without impacting your entire visitor base ● Failback immediately should you encounter a problem ● Control cookies to maintain stickiness - even during failover Edge server assigns session cookie Cookie used to maintain stickiness 85% 15% 60% of “orange” visitors are being directed to Origin B How Phased Release Works

24. © AKAMAI - EDGE 2017 originB.website.com originA.website.com 100% ● Gradually shift all or a segment of your visitors to test a new experience without impacting your entire visitor base ● Failback immediately should you encounter a problem ● Control cookies to maintain stickiness - even during failover Edge server assigns session cookie Cookie used to maintain stickiness 40% 60% 60% of “orange” visitors are being directed to Origin B How Phased Release Works

25. © AKAMAI - EDGE 2017 How Phased Release Works originB.website.com originA.website.com 100% 100% Edge server assigns session cookie Cookie used to maintain stickiness ● Gradually shift all or a segment of your visitors to test a new experience without impacting your entire visitor base ● Failback immediately should you encounter a problem ● Control cookies to maintain stickiness - even during failover 100% of “orange” visitors are being directed to Origin B

26. © AKAMAI - EDGE 2017 Step 1 – Create Policy Specify Policy Name

27. © AKAMAI - EDGE 2017 Step 2 – Activate Phased Release Cloudlet Inside Property Choose a specific path

28. © AKAMAI - EDGE 2017 Step 3 – Specify Alternate Origin(s) Define Origin Name Define Origin Hostname

29. © AKAMAI - EDGE 2017 Step 4 – Configure Logic • Cookie • Device Characteristics • File Extension • Hostname • Query String • Contents of Request Header • URL Path • User Location Choose a specific path Change Origin Apply to a percentage of traffic

30. © AKAMAI - EDGE 2017 Integration Tips • Integrate as part of your Continual Integration • Use Deployment Orchestration software (ie Jenkins or Chef) to control Phased Release as part of your code deployment workflow • Allow monitoring software (ie mPulse) to automatically failback to known good code if a high error rate is detected. • Integration is available via API and coming soon Akamai CLI

31. © AKAMAI - EDGE 2017 Grow revenue opportunities with fast, personalized web experiences and manage complexity from peak demand, mobile devices and data collection. Use CaseDistribute traffic across different data centers

32. © AKAMAI - EDGE 2017 ORIGIN DATACENTERS Multi-region / multi-cloud origin architectures Apps with high availability at the session level on-premise systems private cloud public cloud hybrid cloud PERFORMANCE Application Load Balancer Cloudlet

33. © AKAMAI - EDGE 2017 is a multi-layer load balancer leveraging attributes from both the application layer (Layer 7) and the DNS layer (Layer 3) providing control over traffic directed to various data sources. Session Stickiness Cookie Based Session Stickiness maintains control for consistent session stickiness behaviors Origin Health Checks Origin Health Checks w/ Seamless Failover and Outage Response No Hardware, No Code Reduce complexity & offload routing logic from your data tier to Akamai Fast, Intelligent Routing Akamai’s SureRoute algorithm provides high availability and instant scale through dynamic route optimization and failover logic* Easy to Setup Easy to use interface, and included API, allow you to click to design and activate policies and/or extend cloudlet controls to operations staff Application Load Balancer * SureRoute is only available for accelerated delivery products ©2017 AKAMAI | FASTER FORWARDTM

34. © AKAMAI - EDGE 2017 How we get started • For each Data Center/Origin we define: • Hostname • Location • Load target • Liveliness test • Activate Load Balancing setup in Property Manager

35. © AKAMAI - EDGE 2017 Common Use Case 1 Three private data-centers spread throughout Europe. Running active/active. Session stickiness very important as is failover.

36. © AKAMAI - EDGE 2017 Application Load Balancer Load Balancing Use Case: Multiple DCs + Session Stickiness + Failover Rule A Load Balancing Setup 1 Serve r 1 Serve r 2 LTM Data Center UK Serve r 1 Serve r 2 LTM Data Center Spain Serve r 1 Serve r 2 LTM Data Center Germany HTTP Layer Based Rules: • User location data • URL path • Ex. Micro services URL routing • Cookie • Device characteristics • Ex. Mobile users • File Extensions • Etc. Simple Application Load Balancer Setup - one rule and one load balancing setup LTM  Local Traffic Manager (ex. F5)

37. © AKAMAI - EDGE 2017 Application Load Balancer Load Balancing Use Case: Multiple DCs + Session Stickiness + Failover Rule A Load Balancing Setup 1 Serve r 1 Serve r 2 LTM Data Center UK Serve r 1 Serve r 2 LTM Data Center Spain Serve r 1 Serve r 2 LTM Data Center Germany Client makes a request from UK 1

38. © AKAMAI - EDGE 2017 Application Load Balancer Load Balancing Use Case: Multiple DCs + Session Stickiness + Failover Rule A Load Balancing Setup 1 Serve r 1 Serve r 2 LTM Data Center UK Serve r 1 Serve r 2 LTM Data Center Spain Serve r 1 Serve r 2 LTM Data Center Germany Client makes a request from UK 1 Request matches to Rule A that includes user location data based on country with the client connecting IP address 2

39. © AKAMAI - EDGE 2017 Application Load Balancer Load Balancing Use Case: Multiple DCs + Session Stickiness + Failover Rule A Load Balancing Setup 1 Serve r 1 Serve r 2 LTM Data Center UK Serve r 1 Serve r 2 LTM Data Center Spain Serve r 1 Serve r 2 LTM Data Center Germany Client makes a request from UK 1 Request matches to Rule A that includes user location data based on country with the client connecting IP address 2 Rule A is associated with Load Balancing Setup 1 which uses performance load balancing to send request to closest data center 3

40. © AKAMAI - EDGE 2017 Application Load Balancer Load Balancing Use Case: Multiple DCs + Session Stickiness + Failover Rule A Load Balancing Setup 1 Serve r 1 Serve r 2 LTM Data Center UK Serve r 1 Serve r 2 LTM Data Center Spain Serve r 1 Serve r 2 LTM Data Center Germany Client makes a request from Spain 1

41. © AKAMAI - EDGE 2017 Application Load Balancer Load Balancing Use Case: Multiple DCs + Session Stickiness + Failover Rule A Load Balancing Setup 1 Serve r 1 Serve r 2 LTM Data Center UK Serve r 1 Serve r 2 LTM Data Center Spain Serve r 1 Serve r 2 LTM Data Center Germany Client makes a request from Spain 1 Request matches to Rule A that includes user location data based on country with the client connecting IP address 2

42. © AKAMAI - EDGE 2017 Application Load Balancer Load Balancing Use Case: Multiple DCs + Session Stickiness + Failover Rule A Load Balancing Setup 1 Serve r 1 Serve r 2 LTM Data Center UK Serve r 1 Serve r 2 LTM Data Center Spain Serve r 1 Serve r 2 LTM Data Center Germany Client makes a request from Spain 1 Request matches to Rule A that includes user location data based on country with the client connecting IP address 2 Rule A is associated with Load Balancing Setup 1 which uses performance load balancing to send request to closest data center 3

43. © AKAMAI - EDGE 2017 Application Load Balancer Load Balancing Use Case: Multiple DCs + Session Stickiness + Failover Rule A Load Balancing Setup 1 Serve r 1 Serve r 2 LTM Data Center UK Serve r 1 Serve r 2 LTM Data Center Spain Serve r 1 Serve r 2 LTM Data Center Germany 1 Client makes a request from Germany

44. © AKAMAI - EDGE 2017 Application Load Balancer Load Balancing Use Case: Multiple DCs + Session Stickiness + Failover Rule A Load Balancing Setup 1 Serve r 1 Serve r 2 LTM Data Center UK Serve r 1 Serve r 2 LTM Data Center Spain Serve r 1 Serve r 2 LTM Data Center Germany Request matches to Rule A that includes user location data based on country with the client connecting IP address 2 1 Client makes a request from Germany

45. © AKAMAI - EDGE 2017 Application Load Balancer Load Balancing Use Case: Multiple DCs + Session Stickiness + Failover Rule A Load Balancing Setup 1 Serve r 1 Serve r 2 LTM Data Center UK Serve r 1 Serve r 2 LTM Data Center Spain Serve r 1 Serve r 2 LTM Data Center Germany Request matches to Rule A that includes user location data based on country with the client connecting IP address 2 Rule A is associated with Load Balancing Setup 1 which uses performance load balancing to send request to closest data center 3 1 Client makes a request from Germany

46. © AKAMAI - EDGE 2017 Application Load Balancer Load Balancing Use Case: Multiple DCs + Session Stickiness + Failover Rule A Load Balancing Setup 1 Serve r 1 Serve r 2 LTM Data Center UK Serve r 1 Serve r 2 LTM Data Center Spain Serve r 1 Serve r 2 LTM Data Center Germany Data Center in UK goes down: (e.g. maintenance, outage, etc.)

47. © AKAMAI - EDGE 2017 Application Load Balancer Load Balancing Use Case: Multiple DCs + Session Stickiness + Failover Rule A Load Balancing Setup 1 Serve r 1 Serve r 2 LTM Data Center UK Serve r 1 Serve r 2 LTM Data Center Spain Serve r 1 Serve r 2 LTM Data Center Germany Automatic Failover Occurs sending UK user to Data Center in Spain

48. © AKAMAI - EDGE 2017 Common Use Case 2 Hybrid setup with two private data centers and cloud instance. Running non-critical assets in the cloud. Session stickiness important as is failover.

49. © AKAMAI - EDGE 2017 Load Balancing Use Case: Cloud Migration Serve r 1 Serve r 2 LTM Data Center 1 Application Load Balancer Serve r 1 Serve r 2 LTM Data Center 2 Rule A Load Balancing Setup 1 includes DC1 & DC2 Rule B Load Balancing Setup 2 includes DC3 & DC4 HTTP Layer Based Rules: • User location data • URL path • Ex. Micro services URL routing • Cookie • Device characteristics • Ex. Mobile users • File Extensions • Etc.

50. © AKAMAI - EDGE 2017 Load Balancing Use Case: Cloud Migration Serve r 1 Serve r 2 LTM Data Center 1 Application Load Balancer Client makes a request to access their online banking 1 Serve r 1 Serve r 2 LTM Data Center 2 Rule A Load Balancing Setup 1 includes DC1 & DC2 Rule B Load Balancing Setup 2 includes DC3 & DC4

51. © AKAMAI - EDGE 2017 Load Balancing Use Case: Cloud Migration Serve r 1 Serve r 2 LTM Data Center 1 Application Load Balancer 1 Serve r 1 Serve r 2 LTM Data Center 2 Rule A Load Balancing Setup 1 includes DC1 & DC2 Rule B Load Balancing Setup 2 includes DC3 & DC4 That request gets matched to Rule A that includes session stickiness 2 Client makes a request to access their online banking

52. © AKAMAI - EDGE 2017 Load Balancing Use Case: Cloud Migration Serve r 1 Serve r 2 LTM Data Center 1 Application Load Balancer 1 Serve r 1 Serve r 2 LTM Data Center 2 Rule A Load Balancing Setup 1 includes DC1 & DC2 Rule B Load Balancing Setup 2 includes DC3 & DC4 That request gets matched to Rule A that includes session stickiness 2 Rule A is associated with Load Balancing Setup 1 which directs traffic to either DC1 or DC2 3 Client makes a request to access their online banking ©2017 AKAMAI | FASTER FORWARDTM

53. © AKAMAI - EDGE 2017 Load Balancing Use Case: Cloud Migration Serve r 1 Serve r 2 LTM Data Center 1 Application Load Balancer Serve r 1 Serve r 2 LTM Data Center 2 Rule A Load Balancing Setup 1 includes DC1 & DC2 Rule B Load Balancing Setup 2 includes DC3 & DC4 1 Client makes a request to view a landing page or marketing website ©2017 AKAMAI | FASTER FORWARDTM

54. © AKAMAI - EDGE 2017 Load Balancing Use Case: Cloud Migration Serve r 1 Serve r 2 LTM Data Center 1 Application Load Balancer Serve r 1 Serve r 2 LTM Data Center 2 Rule A Load Balancing Setup 1 includes DC1 & DC2 Rule B Load Balancing Setup 2 includes DC3 & DC4 1 Client makes a request to view a landing page or marketing website 2 That request gets matched to Rule B that includes specific URL Path ©2017 AKAMAI | FASTER FORWARDTM

55. © AKAMAI - EDGE 2017 Load Balancing Use Case: Cloud Migration Serve r 1 Serve r 2 LTM Data Center 1 Application Load Balancer Serve r 1 Serve r 2 LTM Data Center 2 Rule A Load Balancing Setup 1 includes DC1 & DC2 Rule B Load Balancing Setup 2 includes DC3 & DC4 1 Client makes a request to view a landing page or marketing website 2 That request gets matched to Rule B that includes specific URL Path 3 Rule B is associated with Load Balancing Setup 2 which directs traffic to the cloud provider of choice

56. © AKAMAI - EDGE 2017 Forward Rewrite … helps when converting dynamic URLs to be SEO- friendly clean or semantic URLs … provides conditional visitor access to your content or app based on match rules including users’ IP or Geography … manages flash crowds to your API for native mobile apps & single page web applications Visitor Prioritization … provides a visitor- friendly waiting room application for busy sites with flash crowds Edge Redirector … easily manages and offloads URL redirects API Prioritization Available Cloudlets … helps perform a traffic split w/ cookies for A/B testing w/ session stickiness Request Control Audience Segmentation … helps protect your site from behavioral or brute force attacks through misuse of web forms Input Validation … helps facilitate a fast rollout of code changes to production with real users and the ability to failback Phased Release

63. © AKAMAI - EDGE 2017 Grow revenue opportunities with fast, personalized web experiences and manage complexity from peak demand, mobile devices and data collection.

Cloudlets and DevOps - A Dangerously Powerful Combination to Extend Capabilities to the Edge

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Cloudlets and DevOps - A Dangerously Powerful Combination to Extend Capabilities to the Edge

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