***DISAPPEAR FOR SIX MONTHS***
1. Become a ghost for 6 months.
2. Make everything your fault.
3. Find the beast within you.
4. Throw yourself into pain.
5. Cut out all the excuses.
6. Go all in on yourself.
7. Train like a warrior.
8. Work like a robot.
9. Eat like a king.
10. Reject vices.
11. Transform.
12. Upgrade.
13. Create.
14. Thrive.
15. Win.
“President Tinubu, Your Regime And Cabinet Do Not Need To Be Governing Nigeria Anymore, Because Everything About Your Government Is Based On Lies And Fraud. These Are Nigerians In Morocco Who Were Given Scholarships By The Nigerian Government, Yet Have Been Abandoned And Left Stranded. Now They’re Suffering And Jobless”.~ VeryDarkMan
Just in: “Tinubu you are very Terrible, Bandits are making videos inside Bush and posting it on TikTok and the PRO of Police will do nothing about it but once someone criticizes you all online he will be tracked down and arrested, the hardship is so unbearable” - Nigerian man fumes
PACELC Theorem explained.
What if you not only had to choose between consistency and availability during network partitions but also had to consider latency during normal operations?
This is where the PACELC theorem comes into play.
It introduces an added layer of complexity by addressing trade-offs not just during failure events but also under normal conditions.
PACELC extends beyond the CAP theorem's focus on network partitions, broadening our understanding of trade-offs in distributed systems.
While CAP addresses the choice between Availability (A) and Consistency (C) during a network partition (P), PACELC adds an important factor to our decision-making.
Even when our system is functioning normally without a partition, it requires us to decide how much consistency (C) to trade off against latency (L).
Partition, Availability, Consistency, Else, and Latency are the key components of PACELC.
Let's explore them further.
Partition (P)
As with the CAP theorem, we must decide between consistency (C) and availability (A) in the event of a network partition.
Else (E)
When there is no partition, we must choose between latency (L) and consistency (C).
Why does this matter?
We (engineers) need to optimize systems based on their requirements and the demands of the application. This is where the trade-offs come into play.
For instance, if we had a system like a financial system where data accuracy is paramount, we’d prioritize consistency over latency. Conversely, if the system was something like a CDN where the more important quality is speed, then we’d err on the side of prioritizing latency over consistency.
PACELC presents four possible trade-off configurations:
🔹 PA/EL — prioritize availability and latency over consistency
🔹PA/EC — during a partition, choose availability; else, choose consistency
🔹PC/EL — during a partition, choose consistency; else, choose latency
🔹PC/EC — choose consistency at all times
While PACELC theorem originated from database theory and primarily applies to distributed databases, it also applies to any system where data consistency, latency, and availability must be carefully balanced across distributed nodes.