Google Free Tier Compute Engine Reliability Issue with Ghost

Has anybody else experienced constant per day reliability issues with google cloud ompute engine free tier builds of ghost. I have now twice built google cloud fee tier ghost installations to standard install instructions. Latest ghost version, latest compliant node, ubuntu etc. Absolutely vanilla builds per ghost install instructions.

Everything works, but roughly every 24 hours the compute engine errors out on http requests and i need to reset it. It does not go fallback to an nginx bad gateway issues, the compute engine is just toast.

I initially decided to use an instance schedule to recycle the compute engine every 24 hours. After all it is actually a bit of a joke to suggest a single core and 1gb of memory and networked disk is not going to be problematic running in any kind of contention environment. I initially assumed it was either contention or google faulting long running free tier compute engines.

However, even with the daily reset i am getting intermittent compute engine failures.

Any ideas for how to troubleshoot or similar experiences would be greatly apprecaited.

I’m not a Google Compute user but am not surprised that a free tier of anything has stability problems.

Sometimes the cheapest “pay” versions of services have problems as well.

The simple hard truth is that the compute engine free tier is so miserable in its concept and specification that it is almost an invitation to not use the platform. 1 core and 1gb or memory on shared hardware with potentially high contention and remote balanced hard drives, network attached, is going to struggle with basically anything.

However, once i added a swap space manually things have got more stable - and slower of course. You will not beat the misery once specified. You will pick your poison.

One might suggest cynically that the free tier might be largely valuable as an upselling mandate having tempted enough interest to get you to spend 3-6 months learning google cloud concepts. Inertia to use what you just learnt is what it is.