For most use-cases (indexing denormalised data as documents then running searches against them), there's little difference between the two. The mechanics of how the cluster operates are almost identical.
There are some Elasticsearch features that were part of X-Pack (their commercial offering) so aren't included in the OpenSearch fork. Some of those features are really nice to have and make life much easier; the enrich ingest processor is something I really miss in OpenSearch.
The biggest differences are in the tooling around Elasticsearch. All the observability stuff, the SIEM features, various integrations, and now the AI fluff. I've worked with clients in different sectors and - aside from the observability stuff (which is really nice) - none have had an appetite for any of that.
The OpenSearch team is doing some really cool stuff and the project has come a long way. I'm sure it'll continue to improve. It has a very loyal customer base and even has its own annual event; OpenSearchCon 2024 is next month!
My Mum went through CAR-T for lymphoma earlier this year. It's a brutal therapy but can offer benefits in the long term.
As you mentioned, the big issues are around infections. It completely wipes out the immune system, including all vaccinations. Every vaccination needs to be taken again, once the body is recovered from the initial therapy.
My Mum recently contracted COVID and is in hospital being given Paxlovid. She had COVID a while ago and it was nothing compared to her current state. CAR-T made it significantly worse but will hopefully be worth it in the long term.
I'm saddened by your news but - given what I've experienced with my Mum during her cancer journey - can understand the difficult decision you've made.
I would advise taking a K2 MK7 supplement with D3, or get a supplement that contains both. Personally, I take one capsule a day that contains both 3000IU of D3 and 100μg of K2 MK7.
D3 by itself can cause high calcium levels, to the point of toxicity in very high doses. The K2 moves the calcium from the blood to bones.
I developed a calcification in my arm due to this. My wrist was in pain and I couldn't bend it. Got an x-ray, and boom: what looked like a little ball of bone had appeared.
Stopped taking D3 immediately and my body reabsorbed it, never had it again.
Funny enough, it happened when I was visiting Paris. Got to use Google Translate to explore the French medical system. Fantastic service, people aren't joking! :)
> Personally, I take one capsule a day that contains both 3000IU of D3
Not sure how much D3 you're getting (though starting with 3K IU is a lot) because it's not clear how much gets through the gut. You might want to take some cod liver oil (Ω3 capsules) at the same time -- the fat is believed to improve the still mysterious absorption process.
Typical dosage is a drop of cholecalciferol suspension under the tongue for direct absorption.
The Japanese recipe for fermented soybean, called Natto is an abundant natural source. Not easy to find in the US though. I've found it offline at Japanese groceries and one boutique grocer at an exorbitant price so far.
I had heard that myself but was a bit disappointed in the very mild flavor and coffee-like smell. Needs a bit of soy and mustard to give flavor. Not as odd as people said imho, and more accessible than kimchi. It is gooey however.
Possibly good for prostate health as well. Another reason to try I forgot to mention.
Insulin levels are massively overlooked. You can have normal blood glucose but excessive insulin levels due to insulin resistance, which leads to type 2 diabetes.
As another poster mentioned, it won't happen either invasively or non-invasively any time soon. Insulin levels aren't even part of a standard blood test in most places due to the cost.
Now imagine having that entire responsibility yourself, having to do it all manually. That's what we type 1 diabetics do every day!
The nighttime fluctuations could be legit changes in glucose level, but could also be weird sensor issues. The sensor will often give low readings when lying on it in your sleep. These are referred to as 'compression lows'.
The morning glucose spike you noticed is called the 'dawn phenomenon'. I inject a little insulin every morning to counteract it.
The problem with looking at what something delivers is that the time between taking the action and noticing what was delivered. There's often days, weeks, or even months (especially in the case of going to the gym) between doing something and seeing a difference.
When taking a new action (or new inaction), you can even feel worse before feeling better.
It's a good idea but the temporal component skews everything.
Habit formation, even if it's a new habit of not doing something, is something that's worked for me in the past.
Type 1 diabetic here. My body doesn't produce insulin, so if my glucose level goes up after eating or drinking something, that increase in glucose is a (very) approximate measure of insulin response in someone without type 1 diabetes. Insulin is released/produced/injected in response to glucose level increase (and other signals in someone who doesn't have type 1 diabetes).
In my experience, black coffee is absolutely fine outside of an eating window. I fast for at least 18 hours a day, only drinking black coffee and water when fasting. There was no measurable difference in glucose on occasions when I drank black coffee, vs occasions without (all other things as equal as possible).
It's difficult to tell if IF alone had a change because I also switched to a very low carbohydrate diet at pretty-much the same time. The two combined had a massively positive effect on my diabetes.
My glucose level is much more stable, and A1C is lower. I also use significantly less insulin than a lot of people with type 1 diabetes.
My reason for doing both was to reduce insulin levels as much as possible.
No mention of Grenadier apples, unfortunately. Perhaps understandably so.
They're impossible to find in most shops due to them not storing well and being quite ugly. We have a tree in our garden and the apples are outstanding for pies, crumbles, cobblers, and Charlottes. They can hold their shape well, or turn to a delicious purée if cooked longer.
I've been using Dark Sky for years but I uninstalled it yesterday. Since the acquisition, the native Weather app has been massively upgraded with a lot of Dark Sky's best features and is very good now.
I ran the two in parallel for a few months to compare the alerts and accuracy. Weather won out.
Weird, because for me, in the UK, the weather radar is much, much lower resolution in the Weather app.
Dark Sky app however always had a longstanding bug that it’d never show past radar, only future sliding predictions, so I guess both have their problems.
I'm not convinced it is a bad thing. Good scale, relatively low latency, keeps your infrastructure costs down, and many of the other alerting options (looking at you Datadog and NewRelic) are crazy expensive.
Elasticsearch is fine for time series data. A lot of tasks are actually easier with time series data. You add a field called `@timestamp` to your documents and a lot of analysis becomes possible, like date histograms, date range queries, ML jobs, etc.
Immutable time series data like logs and metrics are a great fit for Elasticsearch due to the way Lucene stores data. Documents in Lucene are immutable so an update in Elasticsearch is creates a new document and places a tombstone marker on the old one. Immutable data means you don't have to tolerate those inefficiencies.
Dashboards don't load the entire dataset by default. I can't remember what the exact default time range is but I think it's ~15 minutes or so. They're fairly quick to render in Kibana.
Elasticsearch is a great tool for observability data (logs, metrics, and APM data). Elastic's tooling makes a lot of this really easy in most cases.
I think you may want to check your mappings/templates. There are a lot of data types for this kind of data and they don't rely on the inverted index that you would use for searching fields. Lucene, which Elasticsearch is built on, has a feature called "doc values" that stores data as column-oriented fields. This makes for the fast aggregations, sorting, and grouping for numeric and text fields.
One of the main strengths of Elasticsearch is that you can use it for searching and aggregating in a single query. But you need to ensure you are searching on fields that are indexed for search and sorting/aggregating on fields that are indexed for that.
There are some Elasticsearch features that were part of X-Pack (their commercial offering) so aren't included in the OpenSearch fork. Some of those features are really nice to have and make life much easier; the enrich ingest processor is something I really miss in OpenSearch.
The biggest differences are in the tooling around Elasticsearch. All the observability stuff, the SIEM features, various integrations, and now the AI fluff. I've worked with clients in different sectors and - aside from the observability stuff (which is really nice) - none have had an appetite for any of that.
The OpenSearch team is doing some really cool stuff and the project has come a long way. I'm sure it'll continue to improve. It has a very loyal customer base and even has its own annual event; OpenSearchCon 2024 is next month!