Serverless patterns
•Transferir como PPTX, PDF•
1 gostou•81 visualizações
Brief overview of serverless concepts and common design patterns
Recomendados
Recomendados
Mais conteúdo relacionado
Mais procurados
Mais procurados (20)
Semelhante a Serverless patterns
Semelhante a Serverless patterns (20)
Último
Último (20)
Serverless patterns
- 1. Serverless Architecture Jesse Butler Cloud Native Advocate, Oracle Cloud Infrastructure Basic Patterns with Serverless
- 2. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Safe Harbor Statement The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.
- 3. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. About Me • Oracle via Sun Microsystems • Responsible for Docker on Solaris, later on Oracle Linux • Some work with Open Containers and CNCF WGs • Now a Cloud Native Advocate @ Oracle Cloud • @jlb13 on Twitter 3
- 4. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. About OCI • Next-generation Cloud Infrastructure • Highly performant, very affordable • Managed Cloud Native Services –OKE & OCIR at the core –Many managed services in the pipeline • Check out OCI: https://cloud.oracle.com/tryit 4
- 5. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Level Set • Serverless • In production? • Lambda? 5
- 6. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Monolithic Applications Users Application Database
- 7. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Monolithic Applications Users Application Database
- 8. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Microservices Load balancer Service Service Database Service Queue Deploying Code to Systems We Build in the Cloud with Excellent Abstractions
- 9. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Serverless Load balancer Service Service Database Service Queue Deploying Code to Systems We Build in the Cloud with Excellent Abstractions
- 10. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 10 Abstractions Decreasing concern (and control) over infrastructure implementation Virtual machines Functions Containers Bare Metal Trend towards Serverless
- 11. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. What Is Serverless? • Event-driven architecture • Invisible infrastructure • Automatic scaling on demand • Fault tolerant and highly available • Granular billing for execution time Confidential – Oracle Internal/Restricted/Highly Restricted11
- 12. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. How Does it Work? 12 Upload Function Source Code Configure Function Trigger Function is invoked when triggered Pay for execution time, not idle time
- 13. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Function Example • Different projects and products differ in use and workflow • This example function can be deployed in Oracle Functions • Just the code, configured against any number of event triggers • As with microservices, applications are composed of many functions
- 14. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 14 Functions-as-a-Service Event Sources Triggers Function Execution Backend Services Business Intelligence Analytics Databases Compute, Network, Storage Kubernetes, Docker, and/or Hypervisor F(n)F(n) F(n) F(n)
- 15. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Oracle Functions 15 Autonomous Platform auto-scales functions No servers to provision, manage Pay Per Use Pay for execution, not for idle time No Lock-in Built on open-source Fn Project and Docker Oracle Functions Functions-as-a-Service Oracle Cloud Integrated Container Native Multi-tenant Secure Open Source Engine
- 16. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Key Features Function Dev KitsOpen Source Engine Oracle Cloud Triggers Events HTTP Timer Streams Container Native Advanced DiagnosticsFine-grained Billing
- 17. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Execution Model • Synchronous • Asynchronous • Streaming
- 18. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Events, Determined by Context • Changes in data • Requests on endpoints • Changes in resources • Timers
- 19. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Using Events • Events or triggers are configured differently • Abstractly, inform the platform to what event(s) should invoke this function • OCI Functions use Cloud Events format for portability
- 20. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. ORACLE CLOUD Use Case: Web and Mobile Backends 20 Identity Process dataTrigger functions Functions Web, Mobile Apps API Platform Mobile Data persisted Database Storage
- 21. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 21 Extend and Enhance Existing Applications ORACLE CLOUD SaaS App Analytics Visualize data Enrich data and send to Analytics service Use data for analytics and insights Inventory create / update Another App Trigger functions Support incident create / update Functions
- 22. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 22 Automation and DevOps ORACLE CLOUD Compute State Change Triggers Storage Other - Check tags - Check security roles - Patch or update - Modify/kill resource - Vulnerability assess Reports/Notifications
- 23. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. ORACLE CLOUD Use Case: Real-Time Stream Processing 23 Messaging/ Streaming Database Perform user sentiment analysis Trigger functions Functions Data from multiple sources – Product Reviews and Ratings, Customer Service Interactions, Social Media, etc. Records saved in database Dashboards with user sentiment analysis trends
- 24. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. ORACLE CLOUD Use Case: Real-Time File Processing 24 Storage Database Generate images of different resolutions and sizes Trigger functions Functions High resolution product image uploaded to storage Storage Images saved in Storage, metadata in Database Generated images displayed on various pages and devices
- 25. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. ORACLE CLOUD Use Case: Batch Processing 25 Database Database Calculate bonus points Functions Utility consumption Storage Bonus points updated Utility bill PDF file Transaction details Scheduled batch job Functions Database Generate utility bill PDF file PDF files saved in Storage Consumption details Scheduled batch job Loyalty bonus receivedCredit card transactions
- 26. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. 26 Internet of Things ORACLE CLOUD Check data against thresholds. If exceeded, raise support incidents, send notifications Ingest Trigger functions Functions Devices and things streaming sensor data Incident created in Service Cloud, notification sent to the technician Mobile Technician App Service Cloud Executive Dashboard
- 27. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Mapping Execution, Events and Architecture • Eventing model is driven by the requirement and context • Choose the right execution model for your application
- 28. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Choose a Pattern that Helps you Minimize • Less is more, good rule of thumb is a single handler per module • Better to proliferate than to decompensate • Observability and triage become infinitely easier at the boundaries
- 29. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Separate and Simplify • Typically consumption of events define application boundaries • Share libraries between functions and applications, not execution context
- 30. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. Separate and Simplify • Don’t worry about cold starts • Do worry about lock-in and data egress
Notas do Editor
- Functions, monitoring, messaging, many managed services
- Audience check
- I’m not here to tell you that monolithic apps are bad. In fact, nice and simple.
- The problem is, they typically contain a lot of complexity and moving parts, all tightly coupled into a blob of stuff Any one change effectively touches the entire body, and everything needs to be tested. This can be expensive. Typically, features get tacked on, along with bug fixes, and that’s where we end up with these long tails on releases. That’s not the best way to get features and fixes out the door fast.
- Let’s reconsider our microservices example With the containers and the kubernetes and al… there’s a lot here that is really infrastructure In solving our business problems, we care about agility, flexibility, robustness… so the separation of concerns and smaller units of code to deploy are good What if that’s all we cared about?
- Serverless is a further abstraction in the cloud With containers and kubernetes, we are decoupled from the host environment, and can abstract many host environments in a distributed mesh with ease With serverless, we abstract even that away, and focus only on our business logic
- There are many definitions, but these are the basic requirements (anyone know what this image is? …. A serverless data center. Haha.)
- How does it work? Upload your code and configuration Set up a trigger – HTTP or Event or Stream or Timer The platform runs your code in response to the trigger You only pay for compute resources used when your code is running, saving the otherwise idle time of containers or VM’s
- Serverless initially defined “client-rich apps” - heavily relied on third-party, cloud-hosted applications and services, to manage server-side logic and state Database, auth services, even frontend – all effectively vendored in This is sometimes known as BaaS – but “serverless” works too And this is still very much an active definition of serverless Another is FaaS, functions… where the backend is implemented in units of deployable functions… and this is what we are typically talking about with AWS Lambda, Azure Functions, Google Cloud Functions, and Oracle Functions
- Event source of all kinds fires functions, which then call into other services as needed
- Managed serverless platform integrated in OCI Based on open source engine, provides a fully managed means of managing and invoking functions at scale Pay per use, granular billing, fully autonomous
- Key features: Open Source FaaS Engine – based on Fn Project Container Native – Docker is a first class citizen. Packages and runs your functions in lightweight docker containers Function Development Kits – Additional set of libraries in Go, Node, Java, Ruby, Python to simplify function development Triggers – HTTP, Events (from Oracle Cloud services like storage, database, apps like RightNow, NetSuite, etc.), Streams (Kakfa, Event Hub Cloud Service), Timer (Cron) Pay per use – fine grained billing, pay for execution time, not for idle time Advanced diagnostics – Platform provides details metrics and execution logs Secure workload isolation Auto scale Highly available
- Sync – fronted by API gateway, typical backend / web app sort of thing Async – events drive these, this is an eventual invocation… image is uploaded, we need to run a handful of functions and maybe store some resulting data… nothing is blocking on it Streaming – messages coming in froma queue, each of which invoke a function o do something needed
- Async functions start for a reason – in a serverless architecture, that reason is codified and delievered to the platofmr, which in turn invokes your code This informs our patterns from the start… something working with imnages which are uploaded will be triggered on data store events, something monitioring infra restources will fire off of change in infra
- Serverless initially defined “client-rich apps” - heavily relied on third-party, cloud-hosted applications and services, to manage server-side logic and state Database, auth services, even frontend – all effectively vendored in This is sometimes known as BaaS – but “serverless” works too And this is still very much an active definition of serverless Another is FaaS, functions… where the backend is implemented in units of deployable functions… and this is what we are typically talking about with AWS Lambda, Azure Functions, Google Cloud Functions, and Oracle Functions
- Use cases: User sentiment analysis, Credit card fraud detection, Product recommendations, Crime detection, etc.
- Sometimes the choice is obvious – it’s an image archiving application, you’re working with storage events Less obvious is something like data processing – batch jobs, streaming? Execution context will inform the configuration – POC is important… sometimes less memory doesn’t mean less money spent…. More memory means you get more cmpute and network contriuved example, but something that takes 5s with 128MB might run in a half second with 1GB and cost nearly the same
- Try to avoid 3000 line “functions” Better to have 30 loosely coupled, functions than 3 fat ones handling it all Better performance in nearly all models with smaller, more discrete functions Boundaries are easy to trace, the less stuff happening between them the better
- Sometimes the choice is obvious – it’s an image archiving application, you’re working with storage events Less obvious is something like data processing – batch jobs, streaming? Execution context will inform the configuration – POC is important… sometimes less memory doesn’t mean less money spent Don’t conflate applications if you can help it – if overall you need to process events from a database and an object store, separate and simplify
- Cold starts are kind of an overwrought thing… typically, if you are getting run frequently enough, it’s not a problem, and if you are very infrequently getting hit, latency sensitivity is the only thing to worry about. There are tricks around that, but for the most part, do you really care about a few seconds startup if you’re only getting hit a few times a day? Lock-in however is real – the only people we hear claiming that this is a myth start with A and end with S and… that’s where the issue is. Data egress alone should be a consideration when selecting a platform. ** Also keep an eye on services you use and how you interact with them is it a standard, de facto or otherwise? is there an open API?