🆕 Lambda SnapStart:

https://aws.amazon.com/blogs/aws/new-accelerate-your-lambda-functions-with-lambda-snapstart/

✻ Lambda SnapStart can improve startup performance for latency-sensitive applications by up to 10x at no extra cost, typically with no changes to your function code. The largest contributor to startup latency (often referred to as cold start time) is the time that Lambda spends initializing the function, which includes loading the function's code, starting the runtime, and initializing the function code.

✻ With SnapStart, Lambda initializes your function when you publish a function version. Lambda takes a Firecracker microVM snapshot of the memory and disk state of the initialized execution environment, encrypts the snapshot, and caches it for low-latency access. When you invoke the function version for the first time, and as the invocations scale up, Lambda resumes new execution environments from the cached snapshot instead of initializing them from scratch, improving startup latency.

⚠️ Important
➣ If your applications depend on uniqueness of state, you must evaluate your function code and verify that it is resilient to snapshot operations. For more information, see Handling uniqueness with Lambda SnapStart.

SnapStart supports:
✅ Java 11 runtime

SnapStart does not support:
❌ provisioned concurrency
❌ arm64
❌ Lambda Extensions
❌ EFS
❌ > 512 MB ephemeral storage

ℹ️ You can't use SnapStart on a function's unpublished version ($LATEST).

SnapStart vs Provisioned Concurrency

👉 Use Provisioned Concurrency if your application has strict cold start latency requirements.
👉 SnapStart helps you improve startup performance by up to 10x at no extra cost.
❗ You can't use both SnapStart and Provisioned Concurrency on the same function version.

#Lambda

💥 EC2 R7iz on Intel Xeon Scalable Gen 4:

https://aws.amazon.com/ec2/instance-types/r7iz/

R7iz
▹ Architecture: x86
▹ Frequency: 3.9 GHz
▹ CPU ⇨ up to 128 vCPUs
▹ Memory ⇨ up to 1 TiB
▹ Network ⇨ up to 50 Gbps
▹ EBS ⇨ up to 40 Gbps

Если вы думаете, что "Intel всё", то нет. Новые виртуалки на свежайшем 4-м поколении Intel на текущий момент становятся самыми мощными для аналитики и других нагрузок, требовательных к памяти.

#EC2

🆕 OpenSearch Serverless 🔥

https://aws.amazon.com/blogs/aws/preview-amazon-opensearch-serverless-run-search-and-analytics-workloads-without-managing-clusters/

Pricing:
🔹 OpenSearch Compute Unit (OCU) - indexing ⇛ $0.24 per OCU per hour
🔸 OpenSearch Compute Unit (OCU) - Search and Query ⇛ $0.24 per OCU per hour
❖ Managed Storage ⇛ $0.024 per GB / month

🆕 Amazon Security Lake:

https://aws.amazon.com/blogs/aws/preview-amazon-security-lake-a-purpose-built-customer-owned-data-lake-service/

Security Lake automatically collects logs for:
√ AWS Health Dashboard
√ CloudTrail
√ Firewall Manager
√ GuardDuty
√ IAM Access Analyzer
√ Inspector
√ Lambda
√ Macie
√ Route 53
√ S3
√ Security Hub
√ Systems Manager Patch Manager
√ VPC

Security Lake automatically partitions and converts incoming log data to a storage and query-efficient Apache Parquet and OCSF format.

Security Lake supports third-party sources providing OCSF security data, including Barracuda Networks, Cisco, Cribl, CrowdStrike, CyberArk, Lacework, Laminar, Netscout, Netskope, Okta, Orca, Palo Alto Networks, Ping Identity, SecurityScorecard, Tanium, The Falco Project, Trend Micro, Vectra AI, VMware, Wiz, and Zscaler.

#Security_Lake

Присоейдиняйтесь прямо сейчас!

https://www.youtube.com/watch?v=dZyDPAZZ_CY

#reinvent

​​AWS re:Invent 2022 обзор анонсов часть 1:

https://www.youtube.com/watch?v=dZyDPAZZ_CY

4:25 Новые Local Zones
8:20 OpenSearch Serverless
11:30 SimSpace Weave
21:57 DataZone
26:52 Security Lake
30:01 Clean Rooms
36:25 Nitro v5
44:17 EC2 C7gn
50:12 EC2 HPC6id
54:43 Lambda SnapStart
58:00 CloudWatch Internet Monitor
1:02:20 Verified Access
1:04:05 ECS Service Connect
1:06:05 Amazon Omics

#reinvent

🆕 New features of Amazon SageMaker:

✺ AutoML step in SageMaker Model Building Pipelines
✺ Collaboration with shared spaces
✺ Data Wrangler data preparation widget
✺ Inference shadow tests
✺ Notebook-based Workflows
✺ SageMaker Model Cards
✺ SageMaker Model Dashboard
✺ SageMaker Role Manager
✺ SageMaker geospatial capabilities
✺ Studio Git extension

#SageMaker #reinvent2022

AWS re:Invent 2022 обзор анонсов часть 2

https://www.youtube.com/watch?v=cbxNxHIkd8M

Присоединяйтесь к нам прямо сейчас!

#reinvent

🆕 AWS Application Composer 🔥

https://aws.amazon.com/blogs/compute/visualize-and-create-your-serverless-workloads-with-aws-application-composer/

◉ Currently, Application Composer supports a limited number of services that we plan to add to in the future.
◉ As a public preview, we are looking for suggestions and ideas to evolve the tool.

https://aws.amazon.com/application-composer/

#Application_Composer

🆕 Amazon EventBridge Pipes:

https://aws.amazon.com/blogs/aws/new-create-point-to-point-integrations-between-event-producers-and-consumers-with-amazon-eventbridge-pipes/

EventBridge Pipes supports the following services as event sources:

✺ DynamoDB
✺ Kinesis
✺ Kafka/MSK
✺ SQS
✺ MQ

#EventBridge_Pipes

​​🆕 Step Functions Distributed Map:

https://aws.amazon.com/blogs/aws/step-functions-distributed-map-a-serverless-solution-for-large-scale-parallel-data-processing/

Step Function’s map state executes the same processing steps for multiple entries in a dataset. The existing map state is limited to 40 parallel iterations at a time.

Glue vs EMR vs S3 Batch Operations

◆ Data scientists and data engineers use Glue and EMR to process large amounts of data.
◆ On the other hand, application developers will use Step Functions to add serverless data processing into their applications. Step Functions is able to scale from zero quickly, which makes it a good fit for interactive workloads where customers may be waiting for the results.
◆ System administrators and IT operation teams are likely to use S3 Batch Operations for single-step IT automation operations such as copying, tagging, or changing permissions on billions of S3 objects.

#Step_Functions #serverless

​​🆕 Amazon CodeCatalyst:

https://aws.amazon.com/blogs/aws/announcing-amazon-codecatalyst-preview-a-unified-software-development-service/

Features in CodeCatalyst to address these challenges include:

▫️ Blueprints that set up the project’s resources—not just scaffolding for new projects, but also the resources needed to support software delivery and deployment.
▫️ On-demand cloud-based Dev Environments, to make it easy to replicate consistent development environments for you or your teams.
▫️ Issue management, enabling tracing of changes across commits, pull requests, and deployments.
▫️ Automated build and release (CI/CD) pipelines using flexible, managed build infrastructure.
▫️ Dashboards to surface a feed of project activities such as commits, pull requests, and test reporting.
▫️ The ability to invite others to collaborate on a project with just an email.
▫️ Unified search, making it easy to find what you’re looking for across users, issues, code and other project resources.

#CodeCatalyst

Amazon CodeCatalyst:
https://codecatalyst.aws/explore

Free Tier:
✅ 2000 Build Minutes
✅ 60 Dev Environment Hours
✅ 10 GB Source Storage
✅ 64 GB Dev Environment Storage

AWS re:Invent 2022 обзор анонсов часть 3:

https://www.youtube.com/watch?v=pNL_uvH_BFU

Присоединяйтесь к нам прямо сейчас!

#reinvent

Доктор Вернер вдохновляет, как всегда! Очень рекомендую посмотреть, много интересных технологий вышло, и все разные, на любой вкус, как говорится! https://www.youtube.com/watch?v=RfvL_423a-I

Top Announcements of AWS re:Invent 2022:

https://aws.amazon.com/blogs/aws/top-announcements-of-aws-reinvent-2022/

#reinvent