What does it mean to be a full-stack developer? Well, according to W3Schools, it means: “a person who can develop both client and server software”.
While I do agree with their definition, I would add that full-stack developers are basically match-makers 🥰. On their own, the frontend and backend are independent and don’t necessarily care about each other. Thus, it is the full-stack developer’s responsibility to make that connection happen and “match them up”. In other words, I believe that full-stack developers are people who know how to send and handle data from the frontend to the backend (and vice versa).
(Think you have a good handle on fetch requests? Skip to the next section!)
“What is fetch?” from the movie Mean Girls
…Not quite 😅
Fetch requests are a huge part of request/response cycles, especially for sending data. With fetch requests we can “get” or “show” information, “post” new information, “patch” (or update) information, and “destroy” information. The basic syntax is as follows (from MDN):
fetch('http://example.com/movies.json') .then(response => response.json()) .then(data => console.log(data));
In our previous posts in this series, we spoke at length about using PgBouncer and Pgpool-II , the connection pool architecture and pros and cons of leveraging one for your PostgreSQL deployment. In our final post, we will put them head-to-head in a detailed feature comparison and compare the results of PgBouncer vs. Pgpool-II performance for your PostgreSQL hosting !
The bottom line – Pgpool-II is a great tool if you need load-balancing and high availability. Connection pooling is almost a bonus you get alongside. PgBouncer does only one thing, but does it really well. If the objective is to limit the number of connections and reduce resource consumption, PgBouncer wins hands down.
It is also perfectly fine to use both PgBouncer and Pgpool-II in a chain – you can have a PgBouncer to provide connection pooling, which talks to a Pgpool-II instance that provides high availability and load balancing. This gives you the best of both worlds!
PostgreSQL Connection Pooling: Part 4 – PgBouncer vs. Pgpool-II
While PgBouncer may seem to be the better option in theory, theory can often be misleading. So, we pitted the two connection poolers head-to-head, using the standard pgbench tool, to see which one provides better transactions per second throughput through a benchmark test. For good measure, we ran the same tests without a connection pooler too.
All of the PostgreSQL benchmark tests were run under the following conditions:
We ran each iteration for 5 minutes to ensure any noise averaged out. Here is how the middleware was installed:
Here are the transactions per second (TPS) results for each scenario across a range of number of clients:
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A Backend for Frontend (BFF) architecture can be used to create backends for client-facing mobile or web apps. BFF’s can help support an application with multiple clients while at the same time moving the system into a less-coupled state than a monolith system. This code pattern helps teams iterate features faster and have control over the backends for mobile apps without affecting the experience for a corresponding mobile or web app.
The backends-for-frontends architectural pattern describes a world in which each client application has its own server-side component — a _backend _for a particular frontend.
This pattern is highly applicable if you have multiple client interfaces with significantly different needs that all consume the same underlying resources. The most common real-world example is an application that has both a web and a mobile client.
To understand why backends-for-frontends is useful, let’s walk through some evolutions in web architecture.
Simplicity is great, right? Actually, it is…but only up to a point. If your application is small enough this architecture can absolutely work! However, monoliths tend to break down with scale. You might hear your teams start to say things like…
These types of problems catalyzed the rise of microservices.
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