F5 Networks offers the Advanced Web Application Firewall (WAF) to provide bot defense, advanced application protection, anti-bot SDK, and other features.
N/A
LaunchDarkly
Score8.7 out of 10
N/A
LaunchDarkly provides a feature management platform that enables DevOps and Product teams to use feature flags at scale. This allows for greater collaboration among team members, and increased usability testing before full-scale feature deployment.
$12
per month
Pricing
F5 Big-IP Advanced WAF
LaunchDarkly
Editions & Modules
No answers on this topic
Foundation
$12
per month per Service Connection per month, or $10 per 1k client-side MAU per mo
Enterprise
Custom
Guardian
Custom
Offerings
Pricing Offerings
F5 Big-IP Advanced WAF
LaunchDarkly
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
Optional
Additional Details
—
Discount available on the Foundation plan for annual pricing.
I believe that in industrial environments like ours where we have to have bare metal devices near the production environment combined with hybrid cloud, that is a good platform. That's a good use case. It optimizes traffic. It helps us stay more secure in our data centers. Now with regards to that are fully operating in the cloud, I'm not really sure if we would make the same decision considering the option that I said to have something that is self-provision to avoid too much management of virtual machines on the cloud. So that's an area of improvement.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
If a new feature should be added but unsure of how it will actually work or how users will accept the new enhancement or change, this tool allows you test and measure initial results. This saves so much time and energy knowing the results before it is deployed and might have low user adoption or acceptance.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
So the product definitely is helping us for sudden attacks through DDOS, some injection ingestion into UI URLs, and definitely it's capturing those and I definitely see that as an advantage for us. They can stop the hackers from using our endpoints.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
A/B or Multi Variant Testing as a methodology to gather insight from customer usage. Experimentation as a feature within LaunchDarkly offers information around the success of one variant over another and whether the experiment has reached statistical significance.
Being able to decouple deployment of code from the release of a feature is hugely valuable.
Development teams are empowered to manage features within their production applications for reliability or testing purposes.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
The UI for events. E.g., clicking the "Accept" button does nothing.
Traffic learning suggestions are often very incorrect. We were originally suggested to use "Automatic" learning, and had to completely scrap the policy due to the suggestions.
"All in one" dashboard for viewing application URL/parameter overrides per policy.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
Most* of it is very intuitive and easy to use. The "Help" section is fairly fantastic. See some of my other comments about things like the "Traffic Learning" section being wildly wrong sometimes, and also the event logs with UI buttons that don't do anything. Overall though, it's an excellent product.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
It's very easy to create new feature flags and set them properly. It is more difficult to get LaunchDarkly integrated within a distributed system so that flags can be used. Especially on stateless servers where gating features by user is not easy. Overall though, it is very easy to get started and I like how simple it is to use.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
From what I have seen, LaunchDarkly integrates well with your code and also services you might have in your tech ecosystem. We use Jenkins for automation and we were able to use it to build pipelines to automate the control of LaunchDarkly toggles in our code.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
-Stable data path equals to less crashes -Almost all the features working as expected -Provides more granular controls in allowing false positives -Request evaluation is accurate -Irules feature is a plus
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
Have used a custom feature flag application created inhouse. All the basic functionality was same as the ones that LaunchDarkly provides. But as time progressed, it required more and more tracking capabilities like which user has turned on/off a feature flag, what are the statuses of different feature flags that are being used across the application etc., So, all and all maintenance of such tracking has become cumbersome.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Improved developer experience with some teams moving to Trunk-based Development.
Increased deployment frequency due to smaller code releases.
Validation of the technical and business value of work is achieved more quickly through smaller pieces of work and through experimenting with a small group of users before a feature gets to 100% of customers.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
