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  1. Stackups
  2. Application & Data
  3. Serverless
  4. Serverless Task Processing
  5. Dkron vs Google Cloud Run

Dkron vs Google Cloud Run

OverviewDecisionsComparisonAlternatives

Overview

Dkron
Dkron
Stacks9
Followers28
Votes0
Google Cloud Run
Google Cloud Run
Stacks291
Followers243
Votes62

Dkron vs Google Cloud Run: What are the differences?

# Key Differences between Dkron and Google Cloud Run

<Write introduction here>

1. **Deployment Scope**: Dkron is a self-hosted, open-source distributed job scheduling system that allows users to run scheduled jobs on their servers. On the other hand, Google Cloud Run is a fully managed platform for deploying containerized applications, providing a serverless experience that abstracts away infrastructure management.
   
2. **Pricing Model**: Dkron is free and open-source, allowing users to utilize the software without any licensing costs. In contrast, Google Cloud Run follows a pay-as-you-go pricing model, where users are charged based on the resources consumed by their applications, providing scalability but potentially higher costs based on usage.
   
3. **Scalability Options**: Dkron primarily focuses on job scheduling and execution, providing scalability in terms of managing a large number of distributed tasks efficiently. Google Cloud Run, on the other hand, offers automatic scaling of container instances based on incoming requests, enabling applications to handle varying levels of traffic dynamically.
   
4. **Maintenance Responsibility**: With Dkron being a self-hosted solution, the users are responsible for maintaining and managing the infrastructure where the system is deployed, including updates and backups. In contrast, Google Cloud Run handles all the infrastructure management tasks, ensuring that users can focus solely on developing and deploying their applications without worrying about maintenance.
   
5. **Ecosystem Integration**: Dkron integrates well with various systems and tools in the DevOps ecosystem, enabling seamless automation of job scheduling and execution processes. Google Cloud Run, being part of the Google Cloud Platform, offers integration with a wide range of Google Cloud services, providing out-of-the-box solutions for building versatile and robust applications.
   
6. **Environment Flexibility**: Dkron allows users to define custom execution environments and configurations for their jobs, offering flexibility in how tasks are executed. In contrast, Google Cloud Run supports deploying applications in any language or environment as long as they are contained within a Docker container, providing a standardized approach to application deployment.

In Summary, Dkron and Google Cloud Run differ in deployment scope, pricing model, scalability options, maintenance responsibility, ecosystem integration, and environment flexibility.

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Advice on Dkron, Google Cloud Run

Clifford
Clifford

Software Engineer at Bidvest Advisory Services

Mar 28, 2020

Decided

Run cloud service containers instead of cloud-native services

  • Running containers means that your microservices are not "cooked" into a cloud provider's architecture.
  • Moving from one cloud to the next means that you simply spin up new instances of your containers in the new cloud using that cloud's container service.
  • Start redirecting your traffic to the new resources.
  • Turn off the containers in the cloud you migrated from.
71.3k views71.3k
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Detailed Comparison

Dkron
Dkron
Google Cloud Run
Google Cloud Run

Dkron is a system service that runs scheduled jobs at given intervals or times, just like the cron unix service but distributed in several machines in a cluster. If a machine fails (the leader), a follower will take over and keep running the scheduled jobs without human intervention.

A managed compute platform that enables you to run stateless containers that are invocable via HTTP requests. It's serverless by abstracting away all infrastructure management.

Executor plugins; Processor plugins; Web UI; Rest API; Job retries; Job chaining; Concurrency control; Historial Metrics; Docker executor; AWS ECS executor; Elasticsearch processor; Advanced Email processor; Embedded storage engine (etcd); Encryption; Web UI Authorization; API Authorization; Dedicated Support
Simple developer experience; Fast autoscaling; Managed; Any language, any library, any binary; Leverage container workflows and standards; Redundancy; Integrated logging and monitoring; Built on Knative; Custom domains
Statistics
Stacks
9
Stacks
291
Followers
28
Followers
243
Votes
0
Votes
62
Pros & Cons
No community feedback yet
Pros
  • 11
    HTTPS endpoints
  • 10
    Pay per use
  • 10
    Fully managed
  • 7
    Concurrency: multiple requests sent to each container
  • 7
    Serverless
Integrations
No integrations available
Google Kubernetes Engine
Google Kubernetes Engine
Google Cloud Build
Google Cloud Build
Docker
Docker
Knative
Knative

What are some alternatives to Dkron, Google Cloud Run?

AWS Lambda

AWS Lambda

AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.

Azure Functions

Azure Functions

Azure Functions is an event driven, compute-on-demand experience that extends the existing Azure application platform with capabilities to implement code triggered by events occurring in virtually any Azure or 3rd party service as well as on-premises systems.

Serverless

Serverless

Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.

Google Cloud Functions

Google Cloud Functions

Construct applications from bite-sized business logic billed to the nearest 100 milliseconds, only while your code is running

Knative

Knative

Knative provides a set of middleware components that are essential to build modern, source-centric, and container-based applications that can run anywhere: on premises, in the cloud, or even in a third-party data center

OpenFaaS

OpenFaaS

Serverless Functions Made Simple for Docker and Kubernetes

Nuclio

Nuclio

nuclio is portable across IoT devices, laptops, on-premises datacenters and cloud deployments, eliminating cloud lock-ins and enabling hybrid solutions.

Apache OpenWhisk

Apache OpenWhisk

OpenWhisk is an open source serverless platform. It is enterprise grade and accessible to all developers thanks to its superior programming model and tooling. It powers IBM Cloud Functions, Adobe I/O Runtime, Naver, Nimbella among others.

Cloud Functions for Firebase

Cloud Functions for Firebase

Cloud Functions for Firebase lets you create functions that are triggered by Firebase products, such as changes to data in the Realtime Database, uploads to Cloud Storage, new user sign ups via Authentication, and conversion events in Analytics.

AWS Batch

AWS Batch

It enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. It dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted.

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