In conclusion, Buildpacks provide an efficient and streamlined approach to container image building and deployment, eliminating the need for lengthy Dockerfiles and complex build pipelines. They operate in two phases: detect and build, automatically detecting the required runtime, framework, and dependencies, and building a container image that is consistent, secure, and ready to deploy.

Paketo Buildpacks are a popular open-source implementation of buildpacks, providing a wide range of pre-built buildpacks for popular languages and frameworks, including Java, Node.js, Go, and more. They offer several benefits, including faster build times, improved security, reduced maintenance, and increased portability.

Using Paketo Buildpacks is a simple process, involving just a few steps, from creating a new project to building and deploying a container image. With Paketo Buildpacks, developers can focus on building great applications, without worrying about the complexities of container image building and deployment.

Phew! We’ve covered a lot of stuff so far. There’s just one more big takeaway I want to share — Abstraction, encapsulation, inheritance, and polymorphism are four of the core principles of object-oriented programming.

So what to take home ?

Abstraction lets us selectively focus on the high-level and abstract way the low-level details.

Inheritance is about code reuse, not hierarchies.

Encapsulation keeps state private so that we can better enforce business rules, protect model invariants, and develop a single source of truth for related data and logic.

Polymorphism provides the ability for us to design for dynamic runtime behaviour, easy extensibility, and substitutability.  

In this chapter, we had an in-depth discussion about consistent hashing, including why it is needed and how it works. The benefits of consistent hashing include:

Minimized keys are redistributed when servers are added or removed.

It is easy to scale horizontally because data are more evenly distributed.

Mitigate hotspot key problem. Excessive access to a specific shard could cause server overload. Imagine data for Katy Perry, Justin Bieber, and Lady Gaga all end up on the same shard. Consistent hashing helps to mitigate the problem by distributing the data more evenly.

Consistent hashing is widely used in real-world systems, including some notable ones:

Partitioning component of Amazon’s Dynamo database [3]

Data partitioning across the cluster in Apache Cassandra [4]

Discord chat application [5]

Akamai content delivery network [6]

Maglev network load balancer [7]

Congratulations on getting this far! Now give yourself a pat on the back. Good job!

In this chapter, we had an in-depth discussion about consistent hashing, including why it is needed and how it works. The benefits of consistent hashing include:

Minimized keys are redistributed when servers are added or removed.

It is easy to scale horizontally because data are more evenly distributed.

Mitigate hotspot key problem. Excessive access to a specific shard could cause server overload. Imagine data for Katy Perry, Justin Bieber, and Lady Gaga all end up on the same shard. Consistent hashing helps to mitigate the problem by distributing the data more evenly.

Consistent hashing is widely used in real-world systems, including some notable ones:

Partitioning component of Amazon’s Dynamo database [3]

Data partitioning across the cluster in Apache Cassandra [4]

Discord chat application [5]

Akamai content delivery network [6]

Maglev network load balancer [7]

Congratulations on getting this far! Now give yourself a pat on the back. Good job!