Apigee Edge is an API management platform now owned and offered by Google, since Google acquired Apigee in 2016.
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AWS Lambda
Score 8.4 out of 10
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AWS Lambda is a serverless computing platform that lets users run code without provisioning or managing servers. With Lambda, users can run code for virtually any type of app or backend service—all with zero administration. It takes of requirements to run and scale code with high availability.
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Pricing
Apigee Edge
AWS Lambda
Editions & Modules
No answers on this topic
128 MB
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1024 MB
$0.0000000167
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10240 MB
$0.0000001667
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Offerings
Pricing Offerings
Apigee Edge
AWS Lambda
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Apigee Edge
AWS Lambda
Features
Apigee Edge
AWS Lambda
API Management
Comparison of API Management features of Product A and Product B
Apigee Edge
9.4
7 Ratings
11% above category average
AWS Lambda
-
Ratings
API access control
9.07 Ratings
00 Ratings
Rate limits and usage policies
9.07 Ratings
00 Ratings
API usage data
9.07 Ratings
00 Ratings
API user onboarding
9.97 Ratings
00 Ratings
API versioning
9.97 Ratings
00 Ratings
Usage billing and payments
9.06 Ratings
00 Ratings
API monitoring and logging
9.97 Ratings
00 Ratings
Access Control and Security
Comparison of Access Control and Security features of Product A and Product B
Few scenarios 1. For viewing API analytics, I think it is best in the market 2. For earning money via API monetization 3. Securing API 4. Onboarding legacy APIs to provide modern REST endpoints
Lambda excels at event-driven, short-lived tasks, such as processing files or building simple APIs. However, it's less ideal for long-running, computationally intensive, or applications that rely on carrying the state between jobs. Cold starts and constant load can easily balloon the costs.
Prohibited from using JSON.stringify on Apigee objects (tokens)
Debugging is difficult
Unable to rename or delete policies without bumping revision
Why would anyone give a js policy one name, display name something else, and script a different name?
'Trace' limited to only 20 transactions
UI allows users to add target servers, but users must utilize the api to turn on SSL.
I'm sure there's more, they just aren't coming to mind right now.
Apigee forgets (expires?) your password at random intervals without notice. Every few weeks, or days, sometimes even three times in one day, I'll attempt to login to Apigee and my password will be 'wrong'. I've reset my password and Apigee still claims it's wrong. I've had to reset my password three times before it finally let me log back in.
Developing test cases for Lambda functions can be difficult. For functions that require some sort of input it can be tough to develop the proper payload and event for a test.
For the uninitiated, deploying functions with Infrastructure as Code tools can be a challenging undertaking.
Logging the output of a function feels disjointed from running the function in the console. A tighter integration with operational logging would be appreciated, perhaps being able to view function logs from the Lambda console instead of having to navigate over to CloudWatch.
Sometimes its difficult to determine the correct permissions needed for Lambda execution from other AWS services.
I am not the one deciding whether to use apigee or not really. But personally, I would recommend the use of it as developing APIs on it is easy. And as a mediator between backend servers, we could easily modify request and responses in it without touching any backend code while having a centralize gateway to access our backend APIs too.
I give it a seven is usability because it's AWS. Their UI's are always clunkier than the competition and their documentation is rather cumbersome. There's SO MUCH to dig through and it's a gamble if you actually end up finding the corresponding info if it will actually help. Like I said before, going to google with a specific problem is likely a better route because AWS is quite ubiquitous and chances are you're not the first to encounter the problem. That being said, using SAM (Serverless application model) and it's SAM Local environment makes running local instances of your Lambdas in dev environments painless and quite fun. Using Nodejs + Lambda + SAM Local + VS Code debugger = AWESOME.
Quite hard to get support, at least on the coding side, when we encounter blockers. But general concerns, they would schedule a call to you for them to get a whole picture of your concern. Albeit in my experience, bad really as they haven't replied about the progress, but otherwise seems to have been fixed.
Amazon consistently provides comprehensive and easy-to-parse documentation of all AWS features and services. Most development team members find what they need with a quick internet search of the AWS documentation available online. If you need advanced support, though, you might need to engage an AWS engineer, and that could be an unexpected (or unwelcome) expense.
Apigee is the best in the market in terms of API Analytics Apigee is having wonderful Documentation with short videos Security is a major concern and Apigee provides an easily configurable policy to secure API Quota and rate-limit is again very easy to configure on every API basis It provides various policies to transform the response from one form to another form e.g. JSON to XML or XML to JSON
AWS Lambda is good for short running functions, and ideally in response to events within AWS. Google App Engine is a more robust environment which can have complex code running for long periods of time, and across more than one instance of hardware. Google App Engine allows for both front-end and back-end infrastructure, while AWS Lambda is only for small back-end functions
As a public entity it is hard to say how much ROI we can have. We have yet to create a billing and ROI plan. We are thinking of other ways to create ROI, possibly through data/service barter.
Positive - Only paying for when code is run, unlike virtual machines where you pay always regardless of processing power usage.
Positive - Scalability and accommodating larger amounts of demand is much cheaper. Instead of scaling up virtual machines and increasing the prices you pay for that, you are just increasing the number of times your lambda function is run.
Negative - Debugging/troubleshooting, and developing for lambda functions take a bit more time to get used to, and migrating code from virtual machines and normal processes to Lambda functions can take a bit of time.