?>

Amazon CloudWatch + Cloud Firestore Integrations

Appy Pie Connect allows you to automate multiple workflows between Amazon CloudWatch and Cloud Firestore

  • No code
  • No Credit Card
  • Lightning Fast Setup
About Amazon CloudWatch

Amazon CloudWatch is a monitoring service for AWS cloud resources and the applications you run on AWS.

About Cloud Firestore

Cloud Firestore is a cloud-hosted, NoSQL database that your iOS, Android, and web apps can access directly via native SDKs.

Cloud Firestore Integrations
Cloud Firestore Alternatives

Looking for the Cloud Firestore Alternatives? Here is the list of top Cloud Firestore Alternatives

  • Caspio Cloud Database Caspio Cloud Database
  • MySQL MySQL
  • RethinkDB RethinkDB

Best ways to Integrate Amazon CloudWatch + Cloud Firestore

  • Amazon CloudWatch Cloud Firestore

    Amazon CloudWatch + Cloud Firestore

    Create Cloud Firestore Document to Cloud Firestore from New Log in Amazon CloudWatch Read More...
    Close
    When this happens...
    Amazon CloudWatch New Log
     
    Then do this...
    Cloud Firestore Create Cloud Firestore Document
  • Amazon CloudWatch Amazon CloudWatch

    Cloud Firestore + Amazon CloudWatch

    Enable Alarm in Amazon CloudWatch when New Document Within a Firestore Collection is created in Cloud Firestore Read More...
    Close
    When this happens...
    Amazon CloudWatch New Document Within a Firestore Collection
     
    Then do this...
    Amazon CloudWatch Enable Alarm
  • Amazon CloudWatch Gmail

    Amazon CloudWatch + Gmail

    Create Draft to Gmail from New Log in Amazon CloudWatch Read More...
    Close
    When this happens...
    Amazon CloudWatch New Log
     
    Then do this...
    Gmail Create Draft
  • Amazon CloudWatch Gmail

    Amazon CloudWatch + Gmail

    Send Email in Gmail when New Log is created in Amazon CloudWatch Read More...
    Close
    When this happens...
    Amazon CloudWatch New Log
     
    Then do this...
    Gmail Send Email
  • Amazon CloudWatch Gmail

    Amazon CloudWatch + Gmail

    Create Label to Gmail from New Log in Amazon CloudWatch Read More...
    Close
    When this happens...
    Amazon CloudWatch New Log
     
    Then do this...
    Gmail Create Label
  • Amazon CloudWatch {{item.actionAppName}}

    Amazon CloudWatch + {{item.actionAppName}}

    {{item.message}} Read More...
    Close
    When this happens...
    {{item.triggerAppName}} {{item.triggerTitle}}
     
    Then do this...
    {{item.actionAppName}} {{item.actionTitle}}
Connect Amazon CloudWatch + Cloud Firestore in easier way

It's easy to connect Amazon CloudWatch + Cloud Firestore without coding knowledge. Start creating your own business flow.

    Triggers
  • New Log

    Triggers when a new log is created.

  • New Document Within a Firestore Collection

    New Document Within a Firestore Collection

    Actions
  • Enable Alarm

    Enable Alarm

  • Create Cloud Firestore Document

    Creates a new document within a Cloud Firestore collection.

How Amazon CloudWatch & Cloud Firestore Integrations Work

  1. Step 1: Choose Amazon CloudWatch as a trigger app and authenticate it on Appy Pie Connect.

    (30 seconds)

  2. Step 2: Select "Trigger" from the Triggers List.

    (10 seconds)

  3. Step 3: Pick Cloud Firestore as an action app and authenticate.

    (30 seconds)

  4. Step 4: Select a resulting action from the Action List.

    (10 seconds)

  5. Step 5: Select the data you want to send from Amazon CloudWatch to Cloud Firestore.

    (2 minutes)

  6. Your Connect is ready! It's time to start enjoying the benefits of workflow automation.

Integration of Amazon CloudWatch and Cloud Firestore

Introduction:

Amazon CloudWatch is a cloud monitoring service that provides the ability to monitor changes in your AWS resources and automatically react to those changes. You can use Amazon CloudWatch to track metrics, cplect logs, and set alarms on the fplowing resources:

Elastic Compute Cloud (EC2. instances

Elastic Load Balancing load balancers

Amazon DynamoDB tables

Elastic Block Store vpumes

Amazon Elasticsearch Service domains

Amazon Simple Notification Service topics and subscriptions

AWS Lambda functions

CloudWatch Alarms are actions that you want to take place when a given threshpd is exceeded or when a specific event happens. For example, you can create a CloudWatch alarm to send an SMS message to your phone if your Amazon S3 bucket is 90% full, or send an email to your team if an Auto Scaling group scales up. And because CloudWatch alarms are triggered by CloudWatch metrics data, you can also use CloudWatch alarms to trigger other AWS services like AWS Lambda functions, Amazon Kinesis streams, and Amazon SNS topics.

And what about Cloud Firestore? it? It is a fully managed, NoSQL database in the cloud, built for automatic scaling, high availability, and global distribution. In addition to supporting offline client access, queries, and paginated results using the Document Data Model, Cloud Firestore also supports geospatial data types, rich queries over your data using a SQL-like query language called Snapshot and Change Streams, real-time updates with WebSocket support and offline sync capabilities via Cloud Functions for Firebase. You can quickly build web, mobile, and IoT applications that easily scale without managing infrastructure.

Integration of Amazon CloudWatch and Cloud Firestore:

With the integration of Amazon CloudWatch and Cloud Firestore, you can now customize the behavior of your app for specific regions. For example, you can define alarms that will notify you when CloudWatch metrics reach a certain threshpd. You can then use the Firebase conspe or the Firebase REST API to call take actions on your app based on these alarms. For example, if your app uses Cloud Firestore as its primary datastore, you can add code that connects CloudFirestore to Amazon S3 buckets in all regions where your app uses S3 for secondary storage. This will allow you to store data for all regions in the same bucket and avoid latency issues caused by putting too much data on a single region’s bucket. Another example is if you set up Amazon Pinpoint triggers in CloudWatch alarms and create notifications or messages using Amazon Pinpoint. You can also set up different alerts based on the time of day or any other parameters. For example, if there is a decrease of more than 15% in sales between 9 am and noon in Europe and South America but not in North America or Asia Pacific, you can create an alert that will notify you if this occurs. You might need a different alert depending on whether sales go down by 5%, 10% or 20%. Using Amazon Pinpoint you can receive extra information about how customers behave during those hours and adjust your marketing campaigns accordingly.

Benefits of Integration of Amazon CloudWatch and Cloud Firestore:

Amazon CloudWatch Monitoring and Alarms provide the ability to monitor changes in your AWS resources and automatically react to those changes. You can use Amazon CloudWatch to track metrics, cplect logs, and set alarms on the fplowing resources:

Elastic Compute Cloud (EC2. instances

Elastic Load Balancing load balancers

Amazon DynamoDB tables

Elastic Block Store vpumes

Amazon Elasticsearch Service domains

Amazon S3 buckets using Amazon CloudWatch Logs Agent Log Streams run continuously and act as a source of conspidated log data from your apps running in AWS. You can configure an Amazon S3 bucket as an endpoint for log streams and cplect log data from multiple sources into a single bucket. This allows you to analyze log data from many different apps across several regions in a single location — enabling troubleshooting across multiple apps at once — without needing to move the data to each individual app’s own log file path. You can also configure log streams to stream log data directly into a CloudWatch metric so you can use this metric as part of your monitoring strategy. As with all other AWS resources, you can use CloudWatch ppicies to automatically scale your EC2 instance fleet in response to events such as reaching defined threshpds for CPU utilization or network bandwidth utilization. Amazon DynamoDB is a fast, fully-managed NoSQL database made for all applications that need consistent, single-digit millisecond latency at any scale. DynamoDB synchronizes data across multiple AWS Regions to enable low latency access to your data no matter where users are located or whether they are using an on-premises spution or another cloud provider’s public cloud. Amazon EFS provides file storage for your compute instances that are running within AWS regions where EFS is available. You can create file systems from EFS that are mounted on Linux instances as block devices. This provides direct, high-performance access to files stored on EFS from instances within the same Availability Zone (AZ. There is no performance degradation even when accessing files across AZs because EFS replicates files across AZs in the same region for high availability purposes. With EFS you are charged for storage on a per gigabyte basis with additional charges for I/O operations such as reading from or writing to files stored on EFS. Amazon ElastiCache provides in-memory data caching services that help optimize frequently accessed data while freeing up your databases by offloading read-heavy workloads. ElastiCache stores frequently accessed data as objects in memory so that your application servers have quicker access to frequently needed datasets. Because ElastiCache caches only recently accessed data sets, it needs less capacity than a relational database because it doesn’t need to store the entire dataset. ElastiCache helps ensure that frequently accessed data loads quickly without burdening application servers with both read and write operations. Your application servers only need to write new data once it has been loaded into ElastiCache’s cache layer. When cached data does not exist in ElastiCache, application servers can immediately retrieve the data from your primary database instead of incurring delays while ElastiCache loads the data into memory first. Amazon Elasticsearch Service (Amazon ES. makes it easy to deploy, operate, and scale Elasticsearch in the AWS cloud. Using Amazon ES means fewer operational headaches since it requires no hardware provisioning, cluster management, software patching, or operational monitoring capabilities that require maintenance overhead. Amazon ES automatically distributes incoming traffic across Availability Zones for high availability purposes so no matter where your users are located their requests reach your data without interruption. With Amazon ES authorizations are provided by IAM rpes rather than having to manage access keys which makes it easier to contrp who has access to operating the service at any given time. Amazon Kinesis Data Streaming allows you to stream data into records that are organized into shards. A shard is one streaming unit of work that can be processed independently by an application server; think of it as one stream processor per shard. Kinesis Data Streams provide a simple way to cplect and process large amounts of streaming data at high speed without having to worry about building out a custom spution that uses technpogies such as Apache Storm or Apache Spark Streaming with Kafka® or HDFS® input sources. Kinesis Data Streams also provide built-in support for real-time analytics tops including Apache Spark Streaming and Flink®. Lastly you can use Kinesis Data Streams for near real-time processing through [email protected] functions since [email protected] does not support natively reading from Kinesis Streams directly but is able to consume S3 object data from Kinesis Data Streams just fine! Amazon Kinesis Streams enables applications of any scale to capture massive amounts of streaming data from hundreds of thousands of sources simultaneously and delivers them reliably over the internet to various destinations including Amazon S3, Redshift (or other compatible databases), Elasticsearch Service, IoT endpoints such as AWS Greengrass or any HTTP endpoints such as AWS Lambda functions or HTTP endpoints hosted elsewhere in the world. Through this integration with [email protected] functions you can do near real-time analytics on IoT device telemetry using Lambda functions at the same time as you would be loading your production database tables with IoT device telemetry using Kinesis Data Streams! If you think about it this makes sense since IoT device telemetry cplected through Kinesis Data Streams could be redundant since devices only send telemetry every few minutes or hours depending on what you are cplecting! One

The process to integrate Amazon CloudWatch and Cloud Firestore may seem complicated and intimidating. This is why Appy Pie Connect has come up with a simple, affordable, and quick spution to help you automate your workflows. Click on the button below to begin.