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Similaire à Low-Latency Data Processing in the Era of Serverless @XP Days
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Low-Latency Data Processing in the Era of Serverless @XP Days
- 1. 1 LOW LATENCY DATA PROCESSING IN THE ERA OF SERVERLESS Nazarii Cherkas | Hazelcast nazarii@hazelcast.com https://twitter.com/n_cherkas
- 3. 3 Brief Agenda • Serverless - Not Just The Lambda Functions? • What do we call Serverless? • Why industry goes Serverless
- 4. 4 Brief Agenda • Serverless - Not Just The Lambda Functions? • What do we call Serverless? • Why industry goes Serverless • Low-Latency Data Processing in Serverless – Any Chance? • Typical scenarios of Low-Latency Processing • What brings the latency in Serverless • Approaches to optimize Serverless Computing
- 5. 5 Brief Agenda • Serverless - Not Just The Lambda Functions? • What do we call Serverless? • Why industry goes Serverless • Low-Latency Data Processing in Serverless – Any Chance? • Typical scenarios of Low-Latency Processing • What brings the latency in Serverless • Approaches to optimize Serverless Computing • Demo Time – The Serverless Fraud Detection
- 6. 6 About me
- 7. 7 About me • 9 years of experience of on different positions from Java Engineer to Team Lead and Solutions Architect @n_cherkas @ncherkas NazariyCherkas1
- 8. 8 About me • 9 years of experience of on different positions from Java Engineer to Team Lead and Solutions Architect • Conference speaker, Program Committee member at Devoxx UA @n_cherkas @ncherkas NazariyCherkas1
- 9. 9 About me • 9 years of experience of on different positions from Java Engineer to Team Lead and Solutions Architect • Conference speaker, Program Committee member at Devoxx UA • Cloud Developer at Hazelcast Inc. @n_cherkas @ncherkas NazariyCherkas1
- 10. 10 About me • 9 years of experience of on different positions from Java Engineer to Team Lead and Solutions Architect • Conference speaker, Program Committee member at Devoxx UA • Cloud Developer at Hazelcast Inc. • Moving you to the Cloud @n_cherkas @ncherkas NazariyCherkas1
- 11. 11 Serverless - Not Just The Lambda Functions
- 12. 12 What do we call Serverless?
- 13. 13 What do we call Serverless? Next step in the Cloud Computing evolution
- 14. 14 What do we call Serverless? Next step in the Cloud Computing evolution
- 15. 15 What do we call Serverless? Next step in the Cloud Computing evolution
- 16. 16 What do we call Serverless? Next step in the Cloud Computing evolution
- 17. 17 What do we call Serverless? Next step in the Cloud Computing evolution
- 18. 18 What do we call Serverless? Next step in the Cloud Computing evolution
- 19. 19 What do we call Serverless? Next step in the Cloud Computing evolution
- 20. 20 What do we call Serverless? Next step in the Cloud Computing evolution
- 21. 21 What do we call Serverless? Significantly use cloud-managed services (BaaS) to manage server- side logic and state
- 22. 22 What do we call Serverless? Significantly use cloud-managed services (BaaS) to manage server- side logic and state Sample BaaS Architecture
- 23. 23 What do we call Serverless? Significantly use cloud-managed services (BaaS) to manage server- side logic and state Sample BaaS Architecture
- 24. 24 What do we call Serverless? Significantly use cloud-managed services (BaaS) to manage server- side logic and state Sample BaaS Architecture
- 25. 25 What do we call Serverless? Significantly use cloud-managed services (BaaS) to manage server- side logic and state Sample BaaS Architecture
- 26. 26 What do we call Serverless? Significantly use cloud-managed services (BaaS) to manage server- side logic and state Sample BaaS Architecture
- 27. 27 What do we call Serverless? Significantly use cloud-managed services (BaaS) to manage server- side logic and state Sample BaaS Architecture
- 28. 28 What do we call Serverless? Significantly use cloud-managed services (BaaS) to manage server- side logic and state Sample BaaS Architecture
- 29. 29 What do we call Serverless? Run code in stateless compute containers (FaaS) that are event- triggered and fully managed by Cloud Provider
- 30. 30 What do we call Serverless? Run code in stateless compute containers (FaaS) that are event- triggered and fully managed by Cloud Provider
- 31. 31 What do we call Serverless? Run code in stateless compute containers (FaaS) that are event- triggered and fully managed by Cloud Provider
- 32. 32 What do we call Serverless? Run code in stateless compute containers (FaaS) that are event- triggered and fully managed by Cloud Provider
- 33. 33 What do we call Serverless? Run code in stateless compute containers (FaaS) that are event- triggered and fully managed by Cloud Provider
- 34. 34 What do we call Serverless? Run code in stateless compute containers (FaaS) that are event- triggered and fully managed by Cloud Provider
- 35. 35 What do we call Serverless? Allows to develop and run applications without thinking about the underlying infrastructure*
- 36. 36 What do we call Serverless? Allows to develop and run applications without thinking about the underlying infrastructure*
- 37. 37 Why industry goes Serverless?
- 38. 38 Why industry goes Serverless? • Lower costs
- 39. 39 Why industry goes Serverless? • Lower costs • Cloud Native
- 40. 40 Why industry goes Serverless? • Lower costs • Cloud Native • Less complexity
- 41. 41 Why industry goes Serverless? • Lower costs • Cloud Native • Less complexity • Significantly reduced time to market
- 42. 42 Low-Latency Data Processing in Serverless – Any chance?
- 43. 43 Typical scenarios of Low-Latency Processing
- 44. 44 Typical scenarios of Low-Latency Processing • Algorithmic trading in Financial markets
- 45. 45 Typical scenarios of Low-Latency Processing • Algorithmic trading in Financial markets • Real-time Bidding for Ads
- 46. 46 Typical scenarios of Low-Latency Processing • Algorithmic trading in Financial markets • Real-time Bidding for Ads • Fraud detection for the in-flight transactions
- 47. 47 Typical scenarios of Low-Latency Processing • Algorithmic trading in Financial markets • Real-time Bidding for Ads • Fraud detection for the in-flight transactions • Personalized user experience in E-commerce
- 48. 48 What brings the latency in Serverless
- 49. 49 What brings the latency in Serverless Lambda Function Lifecycle
- 50. 50 What brings the latency in Serverless Lambda Function Lifecycle
- 51. 51 What brings the latency in Serverless Lambda Function Lifecycle
- 52. 52 What brings the latency in Serverless Lambda Function Lifecycle
- 53. 53 What brings the latency in Serverless Lambda Function Lifecycle
- 54. 54 What brings the latency in Serverless Lambda Function Lifecycle
- 55. 55 What brings the latency in Serverless Lambda Function Lifecycle
- 56. 56 What brings the latency in Serverless Lambda Function Lifecycle
- 57. 57 Approaches to optimize Serverless Computing
- 58. 58 Approaches to optimize Serverless Computing Making periodic requests to the Functions to keep them “Warm”
- 59. 59 Approaches to optimize Serverless Computing Making periodic requests to the Functions to keep them “Warm”
- 60. 60 Approaches to optimize Serverless Computing Pre-Allocating memory for CPU-bound tasks
- 61. 61 Approaches to optimize Serverless Computing Pre-Allocating memory for CPU-bound tasks
- 62. 62 Approaches to optimize Serverless Computing Using co-located services
- 63. 63 Approaches to optimize Serverless Computing Using co-located services
- 64. 64 Approaches to optimize Serverless Computing Using co-located services
- 65. 65 Approaches to optimize Serverless Computing Caching “hot” data in the external In-Memory Store
- 66. 66 Approaches to optimize Serverless Computing Caching “hot” data in the external In-Memory Store
- 67. 67 Approaches to optimize Serverless Computing Caching “hot” data in the external In-Memory Store Latency Numbers Every Programmer Should Know https://people.eecs.berkeley.edu/~rcs/research/interactive_latency.html Read 1 MB sequentially from disk 1 ms
- 68. 68 Approaches to optimize Serverless Computing Caching “hot” data in the external In-Memory Store Latency Numbers Every Programmer Should Know https://people.eecs.berkeley.edu/~rcs/research/interactive_latency.html Read 1 MB sequentially from disk 1 ms Read 1 MB sequentially from SSD 78 μs
- 69. 69 Approaches to optimize Serverless Computing Caching “hot” data in the external In-Memory Store Read 1 MB sequentially from disk 1 ms Read 1 MB sequentially from SSD 78 μs Read 1 MB sequentially from memory 5 μs Latency Numbers Every Programmer Should Know https://people.eecs.berkeley.edu/~rcs/research/interactive_latency.html
- 70. 70 Demo Time The Serverless Fraud Detection
- 71. 71 The Serverless Fraud Detection The Fraud Detection Problem
- 72. 72 The Serverless Fraud Detection The Fraud Detection Problem
- 73. 73 The Serverless Fraud Detection The Fraud Detection Problem
- 74. 74 The Serverless Fraud Detection The Fraud Detection Problem
- 75. 75 The Serverless Fraud Detection Serverless Solution Design
- 76. 76 The Serverless Fraud Detection Serverless Solution Design https://github.com/ncherkas/go-hazelcast-cloud
- 77. 77 The Serverless Fraud Detection Serverless Solution Design https://github.com/ncherkas/go-hazelcast-cloud
- 78. 78 The Serverless Fraud Detection Serverless Solution Design https://github.com/ncherkas/go-hazelcast-cloud
- 79. 79 The Serverless Fraud Detection Why Hazelcast Cloud
- 80. 80 The Serverless Fraud Detection Why Hazelcast Cloud • Managed Service for the Hazelcast IMDG – a full-featured In- Memory Data Grid
- 81. 81 The Serverless Fraud Detection Why Hazelcast Cloud • Managed Service for the Hazelcast IMDG – a full-featured In- Memory Data Grid • Co-located Hazelcast IMDG cluster can transform and ingest data in microseconds (see https://hazelcast.com/resources- type/?type=Benchmark)
- 82. 82 The Serverless Fraud Detection Why Hazelcast Cloud • Managed Service for the Hazelcast IMDG – a full-featured In- Memory Data Grid • Co-located Hazelcast IMDG cluster can transform and ingest data in microseconds (see https://hazelcast.com/resources- type/?type=Benchmark) • Comes with the Enterprise-grade Security
- 83. 83 The Serverless Fraud Detection Why Hazelcast Cloud • Managed Service for the Hazelcast IMDG – a full-featured In- Memory Data Grid • Co-located Hazelcast IMDG cluster can transform and ingest data in microseconds (see https://hazelcast.com/resources- type/?type=Benchmark) • Comes with the Enterprise-grade Security • AWS Lambda-ready
- 84. 84 The Serverless Fraud Detection Other options
- 85. 85 The Serverless Fraud Detection Other options In-Memory Computing Services
- 86. 86 The Serverless Fraud Detection Other options In-Memory Computing Services
- 87. 87 The Serverless Fraud Detection Other options In-Memory Computing Services
- 88. 88 The Serverless Fraud Detection Other options In-Memory Computing Services
- 89. 89 The Serverless Fraud Detection Other options In-Memory Computing Services
- 90. 90 The Serverless Fraud Detection DEMO
- 91. 91 Summary
- 92. 92 Summary • Serverless is a perfect match when you want to move fast
- 93. 93 Summary • Serverless is a perfect match when you want to move fast • You can do Low-Latency Processing in Serverless but be aware of the common pitfalls
- 94. 94 Summary • Serverless is a perfect match when you want to move fast • You can do Low-Latency Processing in Serverless but be aware of the common pitfalls • Think about latency and H/A when you choose the data storage
- 95. 95 Summary • Serverless is a perfect match when you want to move fast • You can do Low-Latency Processing in Serverless but be aware of the common pitfalls • Think about latency and H/A when you choose the data storage • Using the In-Memory Computing helps to reduce the FaaS costs
- 96. 96 Summary • Serverless is a perfect match when you want to move fast • You can do Low-Latency Processing in Serverless but be aware of the common pitfalls • Think about latency and H/A when you choose the data storage • Using the In-Memory Computing helps to reduce the FaaS costs • KEEP CALM and leverage 50$ trial https://console.hazelcast.cloud
Notes de l'éditeur
- 1st this term was introduced with the launch of Amazon Functions and hence is oftent associated with it but IS IT JUST a lambda functions? let’s try to learn more about what it is.
- Cloud computing is the on-demand delivery of compute power, database, storage, applications, and other IT resources via the internet with pay-as-you-go pricing.
- Cloud computing is the on-demand delivery of compute power, database, storage, applications, and other IT resources via the internet with pay-as-you-go pricing.
- Cloud computing is the on-demand delivery of compute power, database, storage, applications, and other IT resources via the internet with pay-as-you-go pricing. Beginning of Mainframes Era when when the giant companies like IBM or HP ruled the industry
- Cloud computing is the on-demand delivery of compute power, database, storage, applications, and other IT resources via the internet with pay-as-you-go pricing.
- Cloud computing is the on-demand delivery of compute power, database, storage, applications, and other IT resources via the internet with pay-as-you-go pricing.
- Cloud computing is the on-demand delivery of compute power, database, storage, applications, and other IT resources via the internet with pay-as-you-go pricing.
- Cloud computing is the on-demand delivery of compute power, database, storage, applications, and other IT resources via the internet with pay-as-you-go pricing.
- Cloud computing is the on-demand delivery of compute power, database, storage, applications, and other IT resources via the internet with pay-as-you-go pricing.
- Serverless applications
- ... At a back-end, you will not manage your own deployment of DB, User Authentication etc. but will be using the Cloud Provider managed services for it
- ... At a back-end, you will not manage your own deployment of DB, User Authentication etc. but will be using the Cloud Provider managed services for it
- ... At a back-end, you will not manage your own deployment of DB, User Authentication etc. but will be using the Cloud Provider managed services for it
- ... At a back-end, you will not manage your own deployment of DB, User Authentication etc. but will be using the Cloud Provider managed services for it
- Serverless allows you to run code in…
- Lambda Function is a compute service that lets you run code without provisioning or managing servers.
- Let’s stop for a while here, question to you guys – what’s the most expensive thing in IT world nowadays? It’s you. And this is why the serverless can save your money. [then story about my friends]
- Mention about elastic scalability So, the Serverless is good for this, for that… but what if we want to solve some really specific problems, e.g. Low-Latency Processing?
- Where the latency comes from in the Serverless?
- Background threads – no possibility to do asynchronous processing TODO: animate red boxes!!!
- What are the ways to solve these problems?
- How to deal with the Cold Start latencies?
- Other case when we can have problems with the performance are the CPU-bound tasks
- Another aspect which impacts the performance is the way we deploy our Serverless system How to deploy the system if we want to minimise a latency?
- At the end, naturally, we may cache the “hot” data - the read-mostly data which is rarely updated.
- Since our “hot” data may not fit the lambda function memory, the external in-memory store is the most common choice for such cases. Why In-Memory Store? TODO: remove “Distributed”?
- TODO: review license So, these numbers talk for themselves – In-Memory Store is what you go for when you need a low-latency data access. Now, after we reviewed various technics how to speed-up the Serverless computing, let’s see how do we apply them in a live demo. NOW, DEMO
- Now, let’s try to use all this in practice and try to solve one of the common low-latency problems – the Fraud Detection Problem
- Why we decided to build Hazelcast Cloud?
- Mention that it will be public-available soon?
- Mention that it is “simple to deploy and use”
- Mention that it is “simple to deploy and use”
- Mention that it is “simple to deploy and use”
- Mention that it is “simple to deploy and use”
- Mention that it is “simple to deploy and use”
- Mention that it is “simple to deploy and use”
- Mention that it is “simple to deploy and use”
- - review s3 function - review validate function - review API GW - review KeepAlive rule - create cluster, meanwhile review code - update functions - enable KeepAlive rule - call validate API P.S. explore logs along way
- Better graph?
- Better graph?
- Better graph?
- Better graph?
- Mention about Amazon FireCracker and Apache OpenWhisk.