Amazon Kinesis Reviews and details

Social recommendations and mentions

• AWS DEV OPS Professional Exam short notes

  When you see Amazon Kinesis as an option, this becomes the ideal option to process data in real time. Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit... - Source: dev.to / about 1 month ago

• Querying microservices in real-time with materialized views

  RisingWave is an open-source streaming database that has built-in fully-managed CDC source connectors for various databases, also it can collect data from other sources such Kafka, Pulsar, Kinesis, or Redpanda and it allows you to query real-time streams using SQL. You can get a materialized view that is always up-to-date. - Source: dev.to / about 1 year ago

• How Streaming database differs from a Traditional database?

  For example, RisingWave is one of the fastest-growing open-source streaming databases that can ingest data from Apache Kafka, Apache Pulsar, Amazon Kinesis, Redpanda, and databases via native Change data capture connections or using Debezium connectors to MySQL and PostgreSQL sources. Previously, I wrote a blog post about how to choose the right streaming database that discusses some key factors that you should... - Source: dev.to / about 1 year ago

• Query Real Time Data in Kafka Using SQL

  RisingWave is an open-source distributed SQL database for stream processing. RisingWave accepts data from sources like Apache Kafka, Apache Pulsar, Amazon Kinesis, Redpanda, and databases via native Change data capture connections to MySQL and PostgreSQL sources. It uses the concept of materialized view that involves caching the outcome of your query operations and it is quite efficient for long-running stream... - Source: dev.to / about 1 year ago

• How to choose the right streaming database

  You can ingest data from different data sources such as message brokers Kafka, Redpanda, Kinesis, Pulsar, or databases MySQL or PostgreSQL using their Change Data Capture (CDC) which is the process of identifying and capturing data changes. - Source: dev.to / about 1 year ago

• Use Golang for data processing with Amazon Kinesis and AWS Lambda

  Amazon Kinesis is a platform for real-time data processing, ingestion, and analysis. Kinesis Data Streams is a serverless streaming data service (part of the Kinesis streaming data platform, along with Kinesis Data Firehose, Kinesis Video Streams, and Kinesis Data Analytics) that enables developers to collect, process, and analyze large amounts of data in real-time from various sources such as social media, IoT... - Source: dev.to / about 1 year ago

• AWS Beginner's Key Terminologies

  Amazon Kinesis (analytics) Amazon Kinesis is a platform for streaming data on AWS. Kinesis offers services that simplify the loading and analysis of streaming data. Https://aws.amazon.com/kinesis/. - Source: dev.to / over 1 year ago

• Data Engineering and DataOps: A Beginner's Guide to Building Data Solutions and Solving Real-World Challenges

  For real-time streaming, we have other frameworks and tools like Apache Kafka, ActiveMQ, and AWS Kinesis. - Source: dev.to / over 1 year ago

• Streamline Your Serverless Development with These Top 10 Powerhouse Tools

  AWS Lambda is a serverless computing platform that lets you run your code in response to events, such as changes to data in an S3 bucket or a new line of a stream in a Kinesis stream. It's a great way to build scalable and cost-effective applications, and it's a must-know tool for any serverless developer. - Source: dev.to / over 1 year ago

• recommend way streaming large file from an apigw-lambda?

  Have you explored Kinesis handing the streaming with events to Lambda to handle storage on the cloud-side? Source: over 1 year ago

• Controlling Elixir supervisors at runtime with feature flags

  Like many applications, our infrastructure relies on queues to decouple various components. In our system we use AWS Kinesis as a data stream, consumed by Broadway consumers for some critical parts of our infrastructure. We have found that sometimes our Broadway consumers for AWS Kinesis fail in ways that do not gracefully recover when they crash. For example, each Kinesis shard has its own supervision tree... - Source: dev.to / almost 2 years ago

• 5 Common Amazon Kinesis Issues

  Amazon Kinesis is the real-time stream processing service of AWS. Whether you got video, audio, or IoT streaming data to handle, Kinesis is the way to go. - Source: dev.to / almost 2 years ago

• Part 4 - Observability and Analytics: The Developer's Guide to Building Notification Systems

  If you’re using a tool like Datadog, you might forward your CloudWatch logs and metrics to Datadog using a Forwarder Lambda function. If you’re also using Kinesis in your tech stack to quickly process streaming data, you can use their Firehose delivery stream to forward logs to Datadog as well. - Source: dev.to / over 2 years ago

• Trigger Lambda Functions with event filtering

  AWS Lambda functions recently announced an enhancement with event-triggers for DynamoDB, Amazon SQS, Amazon Kinesis as event sources which makes it easier for event based Lambda function triggers to get invoked only based on the filter expression. You can read about the official announcement from AWS Blog post. - Source: dev.to / over 2 years ago

• New Axis camera and illuminator setup

  Right now I'm just using Axis Companion with edge storage. I only have Mac computers and don't want to run a VMS so I'm working on some code to stream recordings and analytics metadata to AWS Kinesis. In my personal opinion, edge analytics with cloud storage is the way of the future. I have a basic prototype working but it's not without frustrations. The analytics metadata stream is only available through ONVIF... Source: over 2 years ago

• Creating an Async API using Postgres - Building a Chess Analysis App (Part 3)

  There are a lot of ways to actually implement queues. There are products like Kafka or RabbitMQ. There are managed services like AWS SQS or AWS Kinesis. There are libraries like Celery which can be used with Redis or RabbitMQ. For the workers, you can use serverless functions like AWS Lambda or you can have a pool of servers waiting for work. - Source: dev.to / over 2 years ago

• Getting started with SNS and SQS

  Multiple subscribers are supported for a topic which could be Lambda fns, SQS, Kinesis, HTTP endpoint. The subscribers are not only limited to applications but also email notifications, push notifications on the mobile apps and SMS messages. - Source: dev.to / over 2 years ago

• Daily Chat Thread - August 18, 2021

  Can you refer any good case studies Ive read the one on https://aws.amazon.com/kinesis/. Source: over 2 years ago

• Migrating to AWS

  Over time, we should have only dockers and lambda functions in our compute. While doing this, we should also discard the EC2 instances one by one and move onto Fargate. Drop the Kafka or other messaging services and move to Kinesis, EventBridge, SNS or SQS, as per the requirement. Migrate to cloud native databases like Aurora, DocumentDB, DynamoDB, and other purpose built databases like TimeStream, Keyspace,... - Source: dev.to / almost 3 years ago

• For those running Go in production at scale, what do you use for distributed task queues?

  At work we use AWS Kinesis along with DynamoDB, which is powering the entire production infrastructure stack. Source: almost 3 years ago

• What Skills Do Data Engineers Need - The Data Engineering Skill Pyramid

  Once you have learned about the top three layers and the concepts within them, you can become more specific with your approach. Since you'll have a background in ETLs and data warehousing, and will be accustomed to working with the cloud, setting up something on AWS Kinesis will come more naturally to you. - Source: dev.to / about 3 years ago