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  1. Stackups
  2. Application & Data
  3. Serverless
  4. Serverless Task Processing
  5. Apex vs Serverless

Apex vs Serverless

OverviewDecisionsComparisonAlternatives

Overview

Apex
Apex
Stacks503
Followers117
Votes0
GitHub Stars33
Forks56
Serverless
Serverless
Stacks2.2K
Followers1.2K
Votes28
GitHub Stars46.9K
Forks5.7K

Apex vs Serverless: What are the differences?

<Apex and Serverless are both technologies used in software development. Apex is a programming language used in Salesforce development, while Serverless refers to the execution model where the cloud provider dynamically manages the allocation of machine resources. There are key differences between the two technologies.>

  1. Execution Environment: Apex runs on the Salesforce platform, which provides a dedicated environment for executing code, while Serverless functions are executed in ephemeral containers that are spun up on-demand by cloud providers like AWS or Azure.
  2. Scalability: Apex relies on the resources available within the Salesforce environment for scalability, while Serverless scales automatically based on demand without the need for manual intervention.
  3. Billing Model: In Apex, customers pay for the resources allocated by Salesforce, whereas Serverless follows a "pay-as-you-go" model where customers are only charged for the resources consumed during execution.
  4. Management of Infrastructure: With Apex, developers have limited control over the underlying infrastructure as it is managed by Salesforce, while Serverless allows developers to focus solely on writing code without the need to manage servers or infrastructure.
  5. Event-driven Architecture: Serverless functions are typically event-triggered, responding to specific events or requests, while Apex code in Salesforce is often executed in response to user interactions within the CRM system.
  6. Cold Start Times: In Serverless, there can be a delay in the cold start times when a function is invoked for the first time, compared to Apex where the execution time may be more predictable due to a dedicated environment.

In Summary, the key differences between Apex and Serverless lie in their execution environments, scalability, billing models, infrastructure management, event-driven architectures, and cold start times.

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Advice on Apex, Serverless

Tim
Tim

CTO at Checkly Inc.

Sep 18, 2019

Needs adviceonHerokuHerokuAWS LambdaAWS Lambda

When adding a new feature to Checkly rearchitecting some older piece, I tend to pick Heroku for rolling it out. But not always, because sometimes I pick AWS Lambda . The short story:

  • Developer Experience trumps everything.
  • AWS Lambda is cheap. Up to a limit though. This impact not only your wallet.
  • If you need geographic spread, AWS is lonely at the top.

The setup

Recently, I was doing a brainstorm at a startup here in Berlin on the future of their infrastructure. They were ready to move on from their initial, almost 100% Ec2 + Chef based setup. Everything was on the table. But we crossed out a lot quite quickly:

  • Pure, uncut, self hosted Kubernetes — way too much complexity
  • Managed Kubernetes in various flavors — still too much complexity
  • Zeit — Maybe, but no Docker support
  • Elastic Beanstalk — Maybe, bit old but does the job
  • Heroku
  • Lambda

It became clear a mix of PaaS and FaaS was the way to go. What a surprise! That is exactly what I use for Checkly! But when do you pick which model?

I chopped that question up into the following categories:

  • Developer Experience / DX 🤓
  • Ops Experience / OX 🐂 (?)
  • Cost 💵
  • Lock in 🔐

Read the full post linked below for all details

357k views357k
Comments

Detailed Comparison

Apex
Apex
Serverless
Serverless

Apex is a small tool for deploying and managing AWS Lambda functions. With shims for languages not yet supported by Lambda, you can use Golang out of the box.

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.

Supports languages Lambda does not natively support via shim, such as Go;Binary install (useful for continuous deployment in CI etc);Project level function and resource management;Configuration inheritance and overrides;Command-line function invocation with JSON streams;Transparently generates a zip for your deploy;Function rollback support;Tail function CloudWatchLogs;Concurrency for quick deploys;Dry-run to preview changes
-
Statistics
GitHub Stars
33
GitHub Stars
46.9K
GitHub Forks
56
GitHub Forks
5.7K
Stacks
503
Stacks
2.2K
Followers
117
Followers
1.2K
Votes
0
Votes
28
Pros & Cons
No community feedback yet
Pros
  • 14
    API integration
  • 7
    Supports cloud functions for Google, Azure, and IBM
  • 3
    Lower cost
  • 1
    Auto scale
  • 1
    Openwhisk
Integrations
AWS Lambda
AWS Lambda
Golang
Golang
Azure Functions
Azure Functions
AWS Lambda
AWS Lambda
Amazon API Gateway
Amazon API Gateway

What are some alternatives to Apex, Serverless?

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.

Google Cloud Run

Google Cloud Run

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.

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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