Amazon Timestream
👨💻 AWS Cloud Engineer | Around 6 years of Corporate Experience | Driving Innovation in Cloud Solutions 🔧 Day-to-Day Tasks: Specialize in creating AWS infrastructure for Migration Projects. Leveraging services such as S3, SNS, SQS, IAM, Lambda, System Manager, Kinesis, OpenSearch, Cognito, Storage Gateway, Cloud Watch, API Gateway, AWS Event Scheduler, Secret Manager, ECS, Application Load Balancer, VPC among others. Additionally, I excel in crafting Splunk Dashboards and implementing alerting mechanisms for Cloud Watch logs to monitor failures. My approach involves constructing AWS infrastructure using the Serverless framework and Cloud Formation templates, while automating tasks through Boto3 (Python Scripting) Lambdas. 🎯 Passion: I am deeply passionate about continuously learning new technologies and eagerly anticipate the transformative impact of cloud computing on the tech landscape. 📧 Connect: Feel free to reach out to me at awslearningoals@gmail.com. Let's connect and explore potential collaborations! https://www.linkedin.com/in/rastogiutkarsh/
Amazon Cloud Concepts Learning --> Day26
Amazon Timestream
Time series data is a sequence of data points recorded over a time interval for measuring events that change over time.
You can store and analyze billions of time series data points per day using Amazon Timestream, a serverless time series database that is fully managed, scalable, and designed for this purpose.
Timestream facilitates the efficient management of time series data lifecycles by storing recent data in memory and transferring older data, subject to user-defined criteria, to a cost-optimized storage tier.
It provides query speed up to 1000 times quicker than relational databases at a fraction of the cost. And the only data you pay for is the data you store, query, and consume.
Amazon Timestream Benefits
Serverless with Auto scaling - Timestream automatically scales to accommodate changes in the capacity as your application requires
Data lifecycle management - Timestream is a useful tool for streamlining the intricate data lifecycle management process. With a memory store for recent data and a magnetic store for older data, it provides storage tiering. Based on user-configurable rules, Timestream automates the data transfer from the memory store to the magnetic storage.
Built for time series - You can analyze time series data using SQL, with built-in time series functions for smoothing, approximation, and interpolation.
Always encrypted - Timestream ensures that your time series data is always encrypted, whether at rest or in transit.
High availability - Timestream automatically replicates data and distributes resources across a minimum of three Availability Zones within a single AWS Region to provide high availability for your write and read requests.
Durability - Using Timestream, you can automatically replicate your memory and magnetic store data across several Availability Zones within a single AWS Region
Amazon Timestream Use Cases
IOT Applications - Timestream provides built-in analytic tools, including smoothing, approximation, and interpolation, for analyzing time series data produced by Internet of Things applications.
DevOps Applications - Timestream is perfect for DevOps systems that track health and use indicators and do real-time data analysis to boost availability and performance.
Analytics Applications - Timestream is a tool for large-scale data analysis and storing.
References & Additional Resources
https://docs.aws.amazon.com/timestream/latest/developerguide/what-is-timestream.html
https://aws.amazon.com/timestream/faqs/?nc=sn&loc=5
Note: All Images are from AWS Official Document
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