| 是透過Nagios來進行自動化 |
| 當然得寫成Plugin來處理 |
| 基本原理應該是透過postgres_fdw |
| 把系統紀錄檔轉化為foreign 表格 |
| AWS 工程師有寫了一篇專文來介紹 |
| Working with RDS and Aurora PostgreSQL logs: Part 2 |
| 我要分享的是我寫的程式碼 |
| code是抓取最近的兩個檔案來掃log |
do $$
declare
version_check boolean;
r1 record;
outputinfo varchar(80) := 'N';
chk_interval interval := '00:05';
cnt int;
chk text;
begin
for r1 in SELECT file_name FROM list_postgres_log_files() WHERE file_name LIKE 'postgresql.log.%.csv' ORDER BY 1 DESC LIMIT 2
loop
SELECT create_foreign_table_for_log_file('pglog', 'log_server', r1.file_name) into chk;
select count(*) into cnt
from pglog
where error_severity in ('FATAL','PANIC','WARNNING')
and current_timestamp - log_time <= chk_interval;
drop foreign table pglog;
if cnt > 0
then
raise notice '%',r1.file_name;
end if ;
end loop;
end$$;
| #2020/07/27 |
| 看了 |
| https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/aurora-serverless.how-it-works.html#aurora-serverless.parameter-groups |
| 內的這兩段的文章後 |
| The DB instances in an Aurora Serverless cluster only have associated DB cluster parameter groups, not DB parameter groups. Serverless clusters rely on DB cluster parameter groups because DB instances are not permanently associated with Aurora Serverless clusters. Aurora scales the associated DB instance automatically as needed. The scaling operation involves modifying parameter values to be suitable for the larger or smaller capacity. |
| To customize configuration settings for an Aurora Serverless cluster, you can define your own DB cluster parameter group and modify the parameters it contains. You can modify both cluster-level parameters, and parameters that apply at the instance level in other kinds of Aurora clusters. However, when you modify a DB cluster parameter group that's associated with an Aurora Serverless DB cluster, modifications apply differently than for other DB cluster parameter groups |
| 以及這篇blog文章 |
| https://aws.amazon.com/tw/premiumsupport/knowledge-center/aurora-serverless-logs-enable-view/ |
| By design, Aurora Serverless connects to a proxy fleet of DB instances that scales automatically. Because there isn't a direct DB instance to access and host the log files, you can't view the logs directly from the Amazon Relational Database Service (Amazon RDS) console. However, you can view and download logs that are sent to the CloudWatch console. |
| 我的理解是 |
| serverless FQDN連接的db instance應該是會變的 |
| 所以看log的話除了上傳到cloudwatch的資料外 |
| 當下正在運作的db instance所產出的系統記錄 |
| 應該還是可以透過sql 介面來撈取 |
| 但如果serverless如果因為沒有活動而關閉 |
| 之前的log應該就看不到了 |
| 所以serverless 得online 來watch |